Translation of Methodology of Technology Surveillance in the Universities and Research Centers

The Methodology of Technology Surveillance in Universities and Research Centers 

Abstract 

The technological surveillance is very important at the present time in the development and success of the processes of R&D. It is an organized, selective and permanent process, of capturing information of the exterior and of the own organization it has more than enough science and technology, to select it, to analyze it, to diffuse it and to communicate it, to transform it into knowledge for a better one taking of decisions. The existent methodologies of technological surveillance are characterized, intending a methodology for their application in one university of technical sciences, supported in a technological observatory. It is supplemented with the application of tools of discovery of knowledge based on patents for a research center. The technological surveillance in the Polytechnic Superior Institute of the Havana (CUJAE) with their technological observatory it has allowed to identify strategic programs of investigation, tendencies in the teachings of engineering and architecture, lead in technical and thematic sciences of investigation published in the Web of Science. Additionally maps of knowledge are obtained based on patents applied in the National Center for Scientific Research (CNIC). The implementation of the technological surveillance, their continuous improvement with new tools and their use for the own investigators, favorable the development and increment of programs and strategic lines of investigation (R&D) guided to a pertinent innovation in the engineering and architecture, allowing to identify the evolution in the technological development, what prepares to the university and the investigation centers for the changes in the environment with a strategic focus. 

Keywords: technological surveillance; technological observatory; programs strategic of R&D; map of knowledge of patents. 

INTRODUCTION

Technological surveillance is very important for the success of the R + D + i1 processes. It is defined as “the organized, selective and permanent process of capturing information from outside and of the organization about science and technology, selecting it, analyzing it, disseminating it and communicating it, in order to convert it into knowledge to make decisions with less risk and be able to anticipate changes “2.

The observation and analysis of the scientific and technological environment and of the present and future economic impacts for strategic decision making are part of the technological surveillance3. In the management of technological innovation4, surveillance is part of its processes, together with human resources, collaboration, project management, quality and its indicators. In the literature, different terms have also been adopted that are closely related, such as technological surveillance5,6, technological intelligence7,8,9,10, technological forecasting11,12,13 and technological evaluation11,14. In this article reference will be made to technological surveillance although other meanings are present.

The adequate identification of the source of information is vital for technological surveillance15,16, with web pages increasingly being used, which include patent databases, scientific journals and university portals. The analysis of this information allows to make better decisions and anticipate the systematic changes of the environment17. As a trend, tools appear on the basis of Information Technology and Communications Technologies (ICTs), which is why we talk more about technological intelligence. Several systems are referred to for technological surveillance with the support of ICT, such as those based on methods such as TRIZ, an acronym in Russian for the theory of solving inventive problems, such as CAI (Computer Aided Innovation), for the generation of new concepts , based on scientific and technical knowledge (patent databases, scientific and technical encyclopedias) that analyze emerging technologies for technological forecasting and others are those that are parameterized, according to areas of interest on web pages, generating automatic alerts when detecting a change in one of the indicated web pages, which include Internet search bots, crawlers, spiders or spiders18.

The objective of the article is to characterize some methodologies of technological surveillance with their processes that allow to identify and apply a methodological proposal of technological surveillance in a university of technical sciences, supported by a technological observatory. It shows the use of technological mining to detect technological opportunities in publications and the use of knowledge maps based on patents for a research center.

MATERIALS AND METHODS

As part of the materials and methods, a set of steps is shown to approach the methodological proposal for university and research centers with the identification of the processes and the application of technological surveillance tools (VT).

1. Characterization of existing technological monitoring methodologies in terms of processes and authors that use and disseminate it.

2. Creation of the technological observatory for the university environment.

3. Design, application and analysis of results of guides for technological surveillance according to the source of information and the objective of the university center or

investigation.

Several VT methodologies reported in the literature were analyzed in terms of processes used, shown in Table 1, where FCV means critical surveillance factors.

Morcillo, 200315 Mignogna, 199719 Sánchez et al, 200220 León et al, 200621 Savioz, 20048
Problem and objectives Planning and hypothesis Planning / Identification of needs, FCV Situation or problem, broken down pastedGraphic.png
Sources of Information Internal-external compilation Search and Catch / observe, discover, search, detect, collect, capture Type and source of Information Formulation of information needs
Search for information Search / Information gathering Collection of Information
Analysis of Information Evaluación – Validación 

pastedGraphic_1.png

Analysis and organization / Analyze, Treat and Store Analysis of the information Analysis of the information
Validation of Information Validation and adjustments
Intelligence report Intelligence / added value, influence strategy
Organizational  flows of  internal information, Diffusion Dissemination Communication: to managers, disseminate information, transfer knowledge Diffusion of the Information Dissemination of the Information
Decision making Decision making Decision making/ Strategies Application of the Information
(Porter, et al; 20055; 20079; 20096) Nossella A-, et al, 200822 Vázquez, L. 200923 Norma Francesa de Vigilancia, AFNOR,199824 Norma Española AENOR2
Definition of FCV Identification of resource information Definition of VT plan Identification of critical competitive and technological factors and problems Understanding of request and context. Definition / redefinition of surveillance and purpose axes Identification areas / objectives VT system, availability resources / information, Problem definition
Search and Capture Collection of Data Identification and selection of sources of relevant information. Looking for information Determination of types of information, identification / selection of information sources Identification of Sources 
Collection and selection of information Search
Treatment and Analysis Analysis of data Analysis of Information. Analysis of Results Analysis and Organization Analysis and Organization
Validation and Exploitation Organization / Purpose / implementation Competitive Intelligence Validation and adjustment / Synthesis and perspective Validation of the Information
Diffusion of information Distribution of the Results  Communication of the Results Preparation of a report

Tabla 1. Processes described in technological surveillance methodologies

The methodologies present as the most common processes the search and analysis of information. The other processes vary depending on the scope and purpose of the surveillance and the dissemination that is carried out on the results of the same, including the users, as well as the decision-making process. It is appreciated that the technological surveillance “can be understood as a process, providing information about the technology (intelligence), the prediction of the directions that technological change will take (forecast) or the evaluation and exploration potential of the technologies that an entity must adopt (evaluation) The implementation of an organized system of technological surveillance requires multidisciplinary and horizontal approaches and requires its adaptation to the company’s environment and culture, and must be integrated into its usual procedures25.

TECHNOLOGICAL OBSERVATORY OF THE UNIVERSITY CENTER OF TECHNICAL SCIENCES

The Web can be seen as a wide and searchable virtual library26,21, which is no longer an object of study, only of librarianship or documentation professionals, to become an essential component for research27,28,29,30, even with the application of methods such as Data Envelopment Analysis (DEA) for the evaluation of the efficiency of research groups based on information from the Andalusian Scientific Information System (SICA) 31 or in support of Science and Technology Systems from the use of studies on the information of publications and patents32. All this information on the web has led to the creation of technological observatories.

A Technological Observatory (OT) allows to manage the knowledge of organizations through the monitoring of the scientific and technological environment, to generate new knowledge. It allows to establish links with other organizations to share and receive information. It must be supported on a virtual platform that allows quick access to it and is aimed at the delivery of products or services resulting from the Technological Surveillance process. OT is known as a way to enhance the ability to detect changes and technological advances, with its degree of maturity and market opportunities. It employs techniques of technological surveillance33.

At the “José Antonio Echeverría” Higher Polytechnic Institute (CUJAE), the creation of the Technological Observatory in December 2006 was promoted in support of strategic planning. The OT portal of the CUJAE was designed using free software, with PHP programming language, with MySQL database manager, based on Joomla content management system (CMS) as Web applications to create and administer sites. contents quickly and easily. Among the most important objectives of the OT of the

CUJAE meet: search, analysis and dissemination about teaching, publications and research in technical universities, the monitoring and publication of bulletins related to strategic research lines, the dissemination of personalized databases and the support of strategic decision making in these areas.

EXPERIMENTATION OF TECHNOLOGICAL SURVEILLANCE IN THE CUJAE

The experimentation on technological surveillance in the CUJAE has been carried out since 2007 to the present. Some of the surveillance studies refer to:

• Analysis of international engineering and architecture trends in the top 200 universities in the ranking34.

• The identification of pure and integrated research topics in engineering and architecture.

• The identification of trends in curricula and models of educational management in the world, in particular for engineering and architecture.

• The identification of the strategic research programs of the CUJAE, among which are Information and Communication Technologies (ICT), Environment, Life Sciences and Nanotechnologies.

• The evaluation of innovation indicators of Ibero-American and European countries35. An OT analysis in 2008 with 117 universities from the world’s top 50036 regarding alignment to strategic research programs yields interesting data such as those shown in Figure 1.

Figure 2 shows another analysis performed on the presence of research in Computer Engineering with 71.4% and Chemistry with 37.1% in the first 63 universities in the world ranking, according to the country of the university of origin.

Figure 2. Representation of research in computer engineering and chemistry in the 63 first universities in the world

As an example, table 2 shows some of the research topics found in the first 63 universities in Computer Engineering.

Career Pure Theme Temática integrada
Informatic Engineering Science, engineering, computer design and strategy, software engineering, algorithms, programming languages, database management, data mining, machine learning, systems and computational architecture, information web systems, computer security, cryptography, parallel processing , distributed laboratory for digital libraries, interface analysis, integrated and operational systems, optimization systems, multimedia learning, high performance computing Computational biology, biocybernetics, bioinformatics, genome and computational neuroscience, learning systems, computational mathematics, robotics, control systems, compilers, advanced digital applications, analog-digital integrated circuits, computational dynamics of fluids, wireless systems, communications and networks wireless, computer networks, mobile computing and distributed systems, computational geology, computational dynamics, network control, digital signal processing and conduction, digital art, computer man interaction

Table 2. Some topics of pure and integrated research in Computer Engineering in the first 63 universities

ANALYSIS OF OPPORTUNITIES OF PUBLICATION AND PATENTS IN UNIVERSITY AND RESEARCH CENTERS

The extraction of publication opportunities for mainstream journals, which make available abstracts, authors, years of publication, name of the journal, using techniques of mining technology5 is an application that has begun to be carried out in the CUJAE in 2010. If a concept has decreased over time, it could suggest that it has reached its limit of development and vice versa, which would generate an opportunity for publication. In turn, we can obtain the concept in which we are working with the authors that publish the most, establish contacts with them, know the impact of the citations in the research37 or even define the R & D lines for which we have good own resources38.

The sources of external information that the observatory currently has are the publications and patent databases fundamentally. Many of these databases provide RSS content syndication channels (“Rich Site Summary” or “Really Simple Syndication”) through which you can obtain the information contained in them. They are files in XML format that contain the last elements published by a Web site in a certain subject. Publications are obtained through the ScienceDirect RSS feeds that give free access to the title, the abstract, the authors, the year of publication, the journal, the volume and the number of articles it contains. The patent channels provide metadata such as the title of the patent, the inventor, the year of publication, a summary or description of the invention and the entity where the invention is applied and the scientific news channels allow obtaining the title of the news, the author, the date and a summary. The information provided by these RSS channels are retrieved in a MySQL repository in tables to store the different types of information sources.

A first experimental approach was obtained with all the articles of the Information Systems magazine from 2005 to date, recovering a total of 220 records. Thus, the keywords are obtained from the summary of the article, to which technological mining techniques will be applied. The next minable view that has the fields of title, first author, second author, year and five words is shown in table 3.

Through this information of the minable view, it can be obtained in an initial analysis with visualization techniques: What are the most approached topics ?, What are the leading researchers in a research area ?, What are the trends in the investigation?. In this way, research opportunities are obtained for the university environment. The implementation of this guide for the identification of technological opportunities will be generalized to other impact journals and other sources of information. It is also planned to establish a database with the internal information of the researches carried out, which allows to characterize the internal strengths in terms of scientific research and to be able to focus on journals where the strengths are directly taxed. YALE RapidMiner software will be used, being one of the most used worldwide in techmining, with a very friendly graphic interface.

Other applications of knowledge discovery have been carried out with the use of the Automated System for Patent Surveillance (SiVigPat) 39, such as the study of the development of international patents (United States, Canada and Japan) related to corrosion and the protection40. Thus it was known that the largest number of patent applications are related to chemical additives with a tendency to increase the number of patents in electrochemical protection methods and monitoring from the year 1984. Figure 2 shows the result of the analysis in the fields of selected applications.

CONCLUSIONS

In universities and research centers, it is necessary to implement a technology surveillance methodology that involves as many actors as possible and the use of tools for capturing, analyzing, processing and disseminating information, as well as control indicators for this process and of the strategic research programs themselves.

The Technological Observatory at CUJAE has fostered the development of strategic research programs and lines in the environment of engineering and architecture, allowing the identification of evolution in technological development, which in turn prepares the university for changes in the environment with a strategic focus.

The channels or RSS technology becomes very efficient for obtaining external information (specifically from Science Direct), for technological surveillance in the university environment, together with the technological mining process, favoring clustering, the identification of publishing opportunities and the technological trends.

The use of tools supported in ICT for technological surveillance allows the discovery of useful and relevant knowledge in support of strategies, development and decision making in R + D + i, which was demonstrated with the use of algorithms for the detection of opportunities for publication in the university environment and the use of the SiVigPat by the CNIC for the discovery of patent knowledge, exemplified for patents related to corrosion and protection.

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Translation of Technological Surveillance As A Tool For Information Management: A Literature Review

Technological Surveillance As A Tool For Information Management: A Literature Review

IEEE LATIN AMERICA TRANSACTIONS, VOL. 13, NO. 10, OCTOBER 2015 

L. Back, Universidade Tecnológica Federal do Paraná (UTFPR), Ponta Grossa, Paraná, Brasil, luaniback@hotmail.com 

J. L. Kovaleski, Universidade Tecnológica Federal do Paraná (UTFPR), Ponta Grossa, Paraná, Brasil, kovaleski@utfpr.edu.br 

P. P. Andrade Junior, Universidade Federal de Santa Catarina (UFSC), Ponta Grossa, Paraná, Brasil, pp.andrade@ufsc.br 

I. INTRODUCTION

In order to keep up with the rapid technological development, it is essential that organizations seek strategic partnerships to deal with information management.

In this sense, for this process to occur it is indispensable to identify possibilities and assimilate knowledge of all technological information related to the field of work, since knowledge and articulated information are one of the main means for individuals and organizations to make innovations, becoming or remaining competitive [1], [2], [3]. Among other utilities, the knowledge of the technologies present in the market allows knowing where and from whom to acquire them, in addition to their competencies [4].

In this sense, an alternative to soften the obstacles of the market is to make the organizations follow the technological advance through the dissemination of the technologies, information and means of communication [5]. However, managing information and transforming it into knowledge is a complex activity for organizations. One of the main problems concerns the excess of information, which comprises useless information with no added value and strategic for the organization for decision making. Managing information efficiently can minimize the problems related to excessive information, which makes it difficult and time-consuming to select and acquire relevant knowledge, as well as problems due to the absence of information that can lead to delays and out of date before the market.

The management of scientific and technological information may occur through the technological surveillance of the environment, since this process emphasizes the planning, direction, control and coordination of the development and implementation of information system. Thus, through the identification of events that signify potential opportunities or threats, it is possible to understand technological changes and anticipate them, obtaining competitive and comparative advantages [6]. In this sense, the adequate use of knowledge allows users, who understand the managers of the organizations, to increase their resources and productivity, how to reduce their costs in a substantial way and at the same time allow them to strategically differentiate themselves in the market.

Due to the scarce exploration of the subject of technological surveillance by systematized studies and its importance for the academic and organizational environment, it was decided to build a bibliographic portfolio in order to base and direct future studies. Given this context, this work aims to build a theoretical framework on technological surveillance, identifying its application and benefits generated by its use. In order to reach this goal, it will be necessary to select a relevant bibliographic portfolio on technology surveillance and analyze it, in order to contribute to the scientific advance of the subject and to assist the organizations in the management of their information.

II. METHODOLOGICAL PROCEDURES

This research is defined as descriptive, because it aims to identify a portfolio of articles on the topic of technological surveillance and shed light on its scope and research opportunities. The study is subdivided into three phases, namely: database selection; selection of articles; and analysis of articles.

In order to retain the maximum knowledge on the topic of technological surveillance, a systematic search was made in the literature. The research was conducted in the following databases: Web of Science, Scopus, Science Direct, IEEE Xplore, Scielo and Scholar, because they have relevant indexed journals and are multidisciplinary. The Web of Science database appends most of the most relevant journals published in the world [8].

Key words in Portuguese, English and Spanish were used to search the articles: technological monitoring, technological surveillance, technological surveillance, technological monitoring, technological watch, technological surveillance.

For the screening of articles found the title, keywords and abstract were evaluated, excluding the articles that were in disagreement with the researched topic. When the items evaluated did not contain all the required information, the articles were read completely to decide on their inclusion. The exclusion criterion used included the use of the word technology surveillance for security environment monitoring technologies. The period of analysis of the publications was not defined due to the scarcity of material.

The articles found were exported using the EndNote tool. The EndNote software is a bibliographic reference manager that facilitates the research work and allows the collection of bibliographic references of online databases, importing the metadata and grouping them, forming a virtual library [9]. From this tool it was possible to save the selected articles and filter them according to the criterion of duplicity.

The relevant scientific articles were analyzed through full reading and served as the basis for the construction of literature review.

III. TECHNOLOGICAL SURVEILLANCE

The advance of the market has driven the technological development, a factor that also results from the economic competitiveness, essential for the organizations that wish to remain in the world market in which survive the strongest competitors [10], [11], [12], [13]. Today, the main engine of growth is knowledge, and to stop it, it is necessary to follow the technological advance that happens at high speed and consequently generates a great amount of information [14], [15].

In order to develop a diversified technological portfolio and remain competitive in the market, it is necessary to construct complex competences, involving various tasks such as searching for promising new technologies, by identifying the evolution of technological factors, observing, analyzing and processing information through technological surveillance [ 16], [17], [18], [19], [20]. This practice, based on scientific and technological studies, allows us to base production processes on the intensive incorporation of knowledge, mainly involving information from articles and patents, in the development of new products and processes [13].

The process of technological surveillance focuses on the innovative behavior, products, processes and technologies of its competitors and / or employees. As well as in evaluating new technologies and their possible impacts on their organization [10], [21]. It is a selective informational / documentary process that gathers and organizes information and documents from a specific area and addressed a specific group of users or a set of users whose interests are related, but different [22]. Can be interpreted as an intelligence methodology technology, or as forecasting technology and even as a technology assessment [23].

Technological surveillance is a systematic and organized effort to observe, train, analyze, accurately disseminate and retrieve information about the achievements in the company’s economic, technological, social and commercial environment that are relevant to the organization in the sense of opportunity or threat this. To this end, surveillance should include the merging of high-level information, communications, collaborative environment, information security and data repository, to provide the necessary capacity for the domain of information, to obtain knowledge and the essential elements for decision-making [24], [25], [26], [22], [27], [10], [21].

This search for information takes place through patent documents, publications, and investigations to know structures, strategies and the importance of specific technologies, as well as the life cycle of a specific technology, using specific tools and techniques. The results should be a tool for knowledge that promotes useful and up-to-date information on different technologies, changes in products, regulations, leadership, research developments and new patents. This information should support decision making, anticipating changes in the environment in which they are inserted and minimizing risks [24], [27], [28].

To carry out coordinated actions for the search, treatment and distribution of information obtained legally, useful to several members of an organization in decision-making process and for strategic reflection, constitutes the process of technological surveillance that generates intelligence to those who use it correctly. ], [27].

Monitoring technology markets allows access to knowledge relevant to effective proposals for the solution of technological needs [29]. Another benefit of this tool is the identification of the scientific technological development, as well as the paradigms faced by the companies before the competitiveness and market demand [4], [21], [30].

From technology surveillance it is possible to obtain information to apply new technologies, create new products and evaluate the possible impacts of an event or change in the environment. Most information to get new ideas lies on the external side of the organization in a complex and abundant way, so it is necessary to organize and systematize them to add value and serve for decision making in the innovation decision-making process. Monitoring information contributes to reducing the number of wrong decisions within a process of research, development and implementation of new products / services on the market, since the information raised encourages these processes [13], [31]. Such organization and processing of information is necessary to define the innovation strategies of organizations that use technology surveillance [10], [32].

Information considered useful should be pertinent to some aspect of the organization’s activity, be absorbed in a timely manner, be accurate and relevant [33]. The dissemination process must be well specified and contribute to strategic decision making, ie it should be considered an activity inherent to the process of technological innovation [24], [ 34]. Watching technologies is not only about covering news, it must cover the whole documentary of the information process, covered with adequate preparation and presentation of all information relevant to the generation of intelligence and decisions consistent with guarantees of success [26]. Competitive intelligence, in turn, consists in using the information raised by technological surveillance, to orientate itself to the market, identifying which of them have greater importance and to reach objectives and goals of the organization [10].

Companies that take advantage of opportunities, based on the results of technological surveillance, have the capacity to understand and acquire knowledge about new technological developments and to respond to the new technologies identified. These companies see in the information collected a proactive way of responding to the technologies and diminishing the threats caused by them [20], [23], 35], [36]. The company can further progress by detecting investment and marketing opportunities so that observation can lead to increased market share [28].

Surveillance activities contribute to the innovation of processes and products since they enable the generation and detection of ideas and new solutions, as well as the application and implementation of new technology. However, this is only possible when the critical factors are dribbled and directed to the success of the technology surveillance tool. These factors are usually characteristic of the sector and the strategy of each company, which should be aligned with the benefits generated by the use of technological surveillance [28], [37], [38].

The main reasons for using a surveillance system are: anticipate changes; reduce risks by detecting threats; to progress by detecting customer dissatisfaction and their needs; innovate through new ideas; and cooperate [25]. For the results of surveillance to contribute to the technological strategy of an organization, it is necessary to identify the technologies that may represent threats; identify technological opportunities and protect the organization’s technological capabilities [21].

It must be made clear that technological surveillance is different from competitive intelligence. Surveillance is based on the ability to collect, analyze and disseminate useful information, which allows the company to predict and adapt to a constantly changing environment and the potential for exploiting technologies [39]. Competitive intelligence, however, concerns the use of this information in a decisive way in decision making, which creates a competitive advantage for the organization vis-à-vis the market [28] [40].

As a result, technology surveillance provides information about technology, predicts the directions that drive technological change, and encourages decision-making by organizations that use it in a planned way. Technological surveillance should provide information on the knowledge being investigated, the available technological solutions, the technologies being studied, identify the inefficient and obsolete technologies, as well as the technological trajectory of the main competing companies and information from the research and innovation centers which generate new technologies.

Systematizing technical information and knowing the solutions taken by other people allows starting from a non-zero basis to create mechanisms and solutions to internal problems [41].

Therefore, in order to obtain the expected results from the technological surveillance process, it is necessary to strictly comply with each stage of its development, so that all necessary information is collected and has value for decision making.

IV. DEVELOPMENT OF TECHNOLOGICAL SURVEILLANCE

The technology surveillance system consists of a set of basic functions, ie observation, analysis, and use. Initially, it focuses on the search for information, capture, calculation and dissemination of this information. Subsequently, it focuses on the treatment, study, discussion and validation of the acquired information. Finally, the third function analyzes the decision making that is usually strategic, based on all the information obtained in previous activities [28]. All these functions, when well systematized, can cover the existing information needs, foster scientific research, as well as keep its professionals up to date and help make decisions with less risk [10], [20], [21].

Within a process of technology surveillance, there are two moments: one in which it presents itself passively and the other in an active way. In the first, the internal and external information is analyzed routinely, in order to find relevant data to contribute to the development of the organization. At the second moment, monitoring takes place, that is, it focuses on the systematic search for pertinent information about aspects previously determined by the organization, so as to offer continuous knowledge about the development and emerging trends of the environment in which they are inserted.

A process of technological surveillance can be divided into 6 stages [22], [31]:

• Identify the needs: The necessary information must be identified by the organization through a self-diagnosis that must contain the current technological situation of the company, its suppliers, competitors and customers. This practice indicates which types of information to look for.

• Identify the sources: Determine which sources can provide the necessary information. They can be formal, such as patents, database or books, and informal, such as visits to fairs, conversations and conferences.

• Means of access: these means are heterogeneous and new services are continually being developed to facilitate the search for information. Among them we have the market studies, searches through the internet, through a database for patents and periodicals.

• Search: in this process it is necessary to analyze the results obtained to check if these correspond to the expected. This search only occurs in selected sources, so that the information is relevant and can be cross-checked with the

information.

• Value of information: this step depends on the volume of information to analyze, the content or nature, its format and structure. It can happen by sorting, counting and crossing information.

• Dissemination of information and results: main knowledge acquired by the organization in order to anticipate changes with less risk in decision making. The periodicity, content and presentation structure of the data should be established.

These steps can be visualized in the schematic representation of the technology surveillance process, Fig.1 

****FIGURE 1 ****

It is important to emphasize the connection between the steps, where each one is highly dependent on the results of the previous step. Developing this sequence of steps does not guarantee the success of surveillance because it is directly related to the quality and value of the information collected, as well as to the organization’s strategy. If this is not intended to include in its future the results obtained, there is no basis in performing these techniques [15].

Another way to execute technological surveillance, following the same principles, is given by UNE 166006 of 2006. This standard proposes a series of processes to identify the needs, sources and means of access to information; search, treatment and validation; information valorization, results, measurement and improvement [42].

One way to improve the techniques used for the development of technological surveillance is to make use of the benchmarking tool, that is, to compare performance, with organizations that already execute surveillance practices efficiently, favoring continuous improvement. This is even more important in areas where technological change is very rapid, such as in information technology, and there are occasional difficulties in accessing this information, either because of lack of knowledge or effective tools [27].

The technologies management tools are useful for the surveillance process, since their knowledge and management allow to optimize the effectiveness of surveillance by knowing better its context, level of development and possible evolution, that facilitate the evaluation of the meaning of any movement or technological development of competitors [28]. There are a number of techniques that are used to manage technologies and that contribute to technological surveillance, such as calibration and technological prospecting, trend analysis, and models of international participation with the scientific and technological community [43].

There is a tendency to evaluate knowledge generated by universities through the study of scientific productions, such as dissertations, theses or articles published in recognized journals [44]. As well as through patents, it is possible to monitor the technological changes and the impact and value of innovation in certain sectors, knowing statistically how much and to what extent the research object was explored [18].

In order for information classified as useful by technological surveillance to be used effectively, it needs to be disseminated in an objective and short-term manner [18]. To shorten the response time and reduce the error in the adequate disclosure of the information the analysis of the information must be performed with a high level of automation and by trained people who have a thorough knowledge of the organization’s objectives and strategies [45].

Effectively implementing technological surveillance techniques can generate numerous benefits for an organization: alerts on changes and scientific development; facilitates the updating of knowledge, pointing to market niches as well as avoiding investing economic and human resources in obsolete areas [15], [21].

The Virtual Observatory of Technology Transfer is a digital platform created in Spain by the University of Alicante. Through this, the Technological Institute of Informatics developed a Technological Surveillance system that supports the strategic decision-making of innovation of the Institute and small and medium enterprises of the Information and Communications Technology sector, which allowed to foment the processes innovations in companies. The Observatory monitors a large number of sources of information from different sources: websites, databases, newsletters, etc., selected according to quality criteria to cover the different types of documents: news, events, patents, scientific articles, regulations , legislation. [46]. 

In order to have such a tool, the observatory has a specific computer infrastructure, consisting of technological surveillance software, which facilitates the structured compilation of information, as well as its classification and indexing, and a proprietary content manager in the which is published and disseminated the information retrieved and facilitates its access and consultation through access to the observatory portal, daily news reception, and restricted access to the system by users [46]. In a study with biogeochemical cycles, the technology was applied and the authors verified that through this tool it was possible to classify any vector of data, regardless of whether the values are numerical or alphanumeric, which allows a number of possibilities such as classifying technologies, patents, companies and inventors, according to inherent characteristics determined by the user [47].

A methodology of technological surveillance requires the participation of professionals, who have knowledge about the topic to watch, validate and feed information and make use of a tool for capture, analysis and processing and dissemination of information [21].

Each stage for the development of a process of technological surveillance must be carried out with caution and fulfilling the stipulated objectives. The information needs need to be clear to all involved, as well as the sources where the search for information will be carried out, so that they are reliable and can achieve the expected results.

To process, store and distribute information, technology is used, but it is the people who interpret and classify it as valuable or not. Therefore, the human factor should be valued, considering the importance of the analysis and the selection of the information that will be disseminated for the users’ decision making [48].

V. FINAL CONSIDERATIONS

The objective of this work was to build a theoretical framework on technological surveillance, identifying its application and benefits generated by its use. For this, a systematic search of the literature was made using the following databases: Web of Science, Scopus, Science Direct, IEEE Xplore, Scielo and Scholar.

Thus, all the articles found by the systematic search were analyzed and carefully selected, according to the approach and link with the theme. By reading the acquired portfolio, it was possible to construct a theoretical reference on technological surveillance.

It is imperative that organizations retain knowledge related to technological changes and discoveries so that they can assess which technologies can be used by them in the short, medium and long term. For this, the information management tool called technological surveillance can be used, which aims to collect, analyze and disseminate information from areas determined by the user in order to assist in decision-making processes.

Technological surveillance is an indispensable tool for the competitiveness of organizations and can be adapted to any branch of work and production systems. In order to achieve the desired results, it is necessary to identify within the organizations the purpose of surveillance, its addressees, aspects to be monitored, the necessary sources, time of response and means of dissemination of results.

By virtue of this, when technological vigilance is developed correctly, with all the steps performed according to the user’s information needs, through reliable sources and by trained professionals, it allows to give an overview of the technological scenario in which the organization is located, highlighting their opportunities and threats.

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Notes on Implementing and Managing eGovernment: An International Text

I’ve been reading Richard Heek’s book Implementing and Managing eGovernment: An International Text as part of my doctoral thesis research and the book is, in a few words, foundational, seminal, required reading for anyone in the field of Innovation and Technology Management with a focus on eGovernment. I highly reccommend it.

Below are two organizational spreadsheets, followed by notes from the book.

Data Stakeholder Governance Considerations

Sample Item Costs for eGovernment Planning

Notes

There may be a focus on problem solving and innovation, and a focus on team-working and flexibility (Hafeez and Savani, 2003). The agencies may be characterized by what is known as a ‘task culture’. 

This hybrid management model argues first for an analysis of current public sector realities; and second for an assessment of which management and e-government system designs will best fit this reality. 

The sectors differ in many ways, including:

their espoused objectives (broader in the public sector); 

their view of ‘customers’ (more holistic in the public sector); 

their relation to ‘customers’ (mixed with roles as citizens and compliers in the public sector)

their accountabilities and perceived stakeholders (broader in the public sector)

their human and technological infra- structure (weaker in the public sector); 

the politicization of their processes (greater in the public sector); 

the scale and nature of competition (smaller and political in the public sector) 

Where decentralized information systems, manual or computerized, are already in place, barriers to centralization may be severe. In order to centralize, changes may need to be made to the organization’s whole information systems architecture: new data fields and formats, new hardware and software, new processes by which to handle data, and new processes by which to make decisions and take actions. 

Differences between the objectives and values (that is, the cultures) of particular groups in the public sector also cause a problem. 

Centralized approaches require the commitment of four key resources – money, time, people, and skills – all in short supply in the public sector. For many public organizations, a centralized approach may not be possible because of financial constraints; because staff are too busy on other things; or because no-one has the confidence or capabilities to undertake the necessary planning and coordination tasks. 

decentralized units develop different ways of working, different mindsets that create quite different views of the world between groups; different jargon used in communication; and different issues and people that are valued. 

aspects of system use such as implementation, operation, troubleshooting and maintenance are also likely to occur more quickly under a decentralized regime. 

Training, maintenance and administration costs also contribute. Large, centralized computing systems are estimated to cost something like one-third to one-half of this amount per user per year (CBR, 2001). 

A decentralized approach may be most economic for public organizations, because it saves on overt input costs. A centralized approach may be most efficient, because it avoids waste and duplication. But a successful hybrid approach may be most effective because it can simultaneously provide: 

  • the control necessary to share key resources (including data), to avoid duplication, and to achieve economies of scale; and
  • the freedom necessary to meet user needs, and to overcome blocks to IT usage and system development. 

US State Department, for example, successful progress on e-government has come from retaining computing and data management architecture under control of a central IT office, while decentralizing systems develop- ment responsibilities 

Division is compatible with – indeed, is defined as – simultaneous centralization and decentralization. It can be seen in the possible division of responsibilities described for systems development. It can also be seen in the division of responsibilities between client and server computers. 

That which we can call a managerial or information systems centralization, reflects Nolan’s (1979) well-known ‘stages of growth’. It shows the gradual increase in managerial attempts to control the information systems (which would include e-government systems) within an organization. Nolan’s model has been criticized for a lack of predictive power and a generality that fails to match individual organizational experience. However, its core sense of increasing managerial engagement with IT does appear sound. 

A decentralized approach will also help to spread IT awareness and skills, and even some understanding of the informational aspect of e-government, in a way that other approaches might not. For some public agencies, it is the lack of just such awareness, skills and under- standing that represents a key barrier to effective use of IT in government. 

there are tensions between the somewhat theoretical notions of organizational rationality, and the more real forces of politics in government. Hence, rational logic may play only a minor role in determining which approach is used. 

For example, the approach adopted will be shaped by the organization’s technology (e.g. whether the computing architecture is already centralized or decentralized); staffing and skills (e.g. what skills are avail- able); management systems and structures (e.g. whether the main organization has a centralized or decentralized structure) and other resources (e.g. the availability of finance). 

Stakeholder values will also play a role, such as their perceptions, their awareness of the costs and benefits of particular approaches, and their historical experi- ences. For instance, the recent experiences of staff with e-government systems create either a satisfaction that is inertial, or a dis- satisfaction that demands change. 

buuuut it is organizational politics and its roots in the self-interest of particular stakeholders that will help determine what management approach to e-government is selected 

Four familiar political constituencies (see Figure 2.2) can be identified, whose conflict or compromise within organizations helps to determine which approach is chosen: senior managers, politicians, IT staff, and mainstream staff. 

Broader political, pressures from the outside world – ranging from national political initiatives to dominant ideologies/philosophies – also play their part. Staff in public sector organizations are subject to continuous external pressures, that include (Barrett and Greene, 2001; Abramson and Morin, 2003): 

  • Pressure to conform to the requirements of external bodies, such as central government bodies and funding agencies. An e-government unit run by central government may, for example, be pushing a department to adopt certain centralized ‘best practices’: see, for example, Box 2.6. 
  • Pressure through (mis)perception of what other organizations are doing, which may be transmitted through informal contacts, management texts and training programs, or dealings with consultancy organizations. 
  • Pressure from private sector IT vendors to purchase particular technologies and systems. 

Chapter 3

eGovernment Strategy 

Centralized e-government strategic planning is a six-step process that, overall, asks: ‘Where
are we now?’, ‘Where do we want to get to?’, and ‘How do we get there from here?’

a successful strategy can develop senior management understanding that e-government systems are information systems not just IT, and build consensus and commitment to a strategic vision for e-government. It permits a fundamental review of the organization’s use of informa- tion and technology, leading to a comprehensive understanding of information systems requirements. 

It also provides a detailed plan of action on e-government for the organization. 

Problems of Federal eGovernment Expenditure in the US 

The 2003 US federal budget identified ‘six chronic problems that limit results from Federal IT spending: 

  • Agencies have automated existing outdated processes, instead of fixing underlying management problems or simplifying agency procedures to take advantage of new e-business and e-government capabilities. 
  • Agencies have made unnecessarily duplicative IT investments. 
  • Inadequate program management – many major IT projects have not met cost,
    schedule and performance goals. 
  • Few agencies have had plans demonstrating the linkage between IT capabilities
    and the business needs of the agency. 
  • Agencies have built individual capabilities that are not interoperable with one
    another. Few IT investments significantly improve mission performance. 
  • Poor IT security – major gaps have existed in agency and Government-wide inforsmation and IT-related security.’ 

e 2003 Federal Enterprise Architecture: A ‘business-based framework for Government-wide improvement … constructed through a collection of interrelated ‘reference models’ designed to facilitate cross-agency analysis and the identification of duplicative investments, gaps, and opportunities for collaboration within and across federal agencies.’ (FEAPMO, 2003)

The Strategic Context for Federal Public Agency eGovernment Strategy in the US 

The 2002 eGovernment Act

The 2002 Federal Information Security Management Act

The 2001 President’s Management Agenda

The 1998 Government Paperwork Elimination Act

The 1996 Clinger-Cohen Act

The 1996 Electronic Freedom of Information Act amendment:

The 1993 Government Performance Results Act:

Where are we now?

An answer would include details of the organization’s current structure and functions; key client groups; existing problems that need to be addressed; and important current and forth- coming factors – particularly policies and political priorities 

Where do we want to get to? 

An answer would include details of the organization’s objectives, and some vision of the future organization that will enable it to overcome current and forthcoming problems, and to achieve its objectives. Finally, it asks, ‘How do we get there?’ This would be achieved through a statement of management strategy about major changes to organizational structure and functions in order to reach its future vision. 

two types of organizational function are derived from the organization’s wider business strategy and prioritized for further investigation: 

  1. Existing organizational functions that are to be retained in order to meet organizational objectives 
  2. New organizational functions that need to be introduced in order to meet organizational objectives.

This is the essence of ‘portfolio’ or ‘program’ management: using criteria to align projects with agency strategy. 

Impact priorities, for example, might be: 

highest savings/financial return on investment

highest public visibility/political return on investment

highest learning/demonstrator effect

strongest focus on existing organizational deficiencies

strongest support to key external client  services (as opposed to internal administrative activities). 

Implementation priorities, for example, might be: 

lowest risk/highest feasibility

lowest cost to implement

fastest time for completion

eGovernment Systems Architecture needs three main components:

  1. A data model showing the structure of unified, organization-wide data to which the e-government systems will have access; often illustrated using an entity-relationship diagram (this and the other diagrams mentioned here are described in greater detail in Chapter 8).
  2. A process model showing the key activities of the organization that the e-government systems will either support or under- take; often illustrated using a process diagram.
  3. A data/process model showing the organization-wide connection between business processes and data entities, and the organization-wide movement of data that e-government systems will enable; often illustrated using a data flow diagram. 

Information engineering

This looks across the whole organization and focuses on two components:
business processes: the individual activities of the organization that help meet public sector objectives. 

data classes: data entities of relevance to the organization that are made up from individual data elements (or attributes). 

Data and process are principally connected, and therefore principally investigated, through the mechanism of decision making and action. 

From this investigation, the entire organization is analyzed into two long lists of business processes and data entities. These are cross-checked through a process/data matrix that shows which processes create or use which data. The data entities and processes can then be grouped together into clusters of data and processes that represent required e-government systems within the organization.

Critical success factors
it starts by asking managers to specify the factors they consider to be critical for the successful performance of particular organizational functions

It is the intention that e-government strategy be shaped by organizational objectives and process/information requirements rather than by technology: 

Determining eGovernment organizational architecture:

As part of the ITSPMO analysis, general strategic decisions may include:

  1. making sure that it is the government rather than the company that steers e-government 
  2. stating the approach to management of organizational change, including a determination of the needs for cultural change
  3. clearly allocating responsibilities for e-government systems development and management
  4. identifying major competency gaps and approaches to closing them through human resource strategies
  5. deciding how back-office procedures may be restructured to support e-government
  6. locating the e-government/IT function within the wider organizational structure
  7. demarcating which services (e.g. systems development, training and systems operation) are to be sourced in-house and outsourced
  8. identifying procedures to be used when tendering for and selecting e-government systems products and services
  9. specifying standard systems development methodologies and tools to be used 
  10. identifying financial approaches to be adopted, such as public–private partnerships.

Strategy Implementation 

Disseminate and Plan eGovernment Actions 

A typical business case for an e-government project might include a statement of project objectives; an estimation of benefits, risks and constraints; and an estimation of resource requirements covering finance, human resources (i.e. jobs and skills), technology, and timescales. Details of project deliverables (i.e. things the e-government projects should produce such as feasibility reports, specification documents, and both interim and final versions of the system) and timetables can be approved at this stage. So, too, can mechanisms for reporting back to the eGovernment Steering Group on progress. 

for personnel training and development, for finance, for technology, etc. There may also be an additional dimension to the matrix – time – showing what is to occur and be paid for within particular financial years. 

Many public organizations also find themselves in situations of constant and largely uncontrollable flux from factors such as changeover in ruling political parties; constant circulation of senior politicians and officials; emergence of new political initiatives and legislation that alter organizational activities, priorities and even structures; sudden imposition of cost- cutting measures; sudden external crises that demand a reaction; changes within the client groups the organizations serve; and changes in IT, IT standards and IT suppliers. 

The Outcome of eGovernment Strategy 

There are many ways for strategies to go wrong:

  • Lack of Strategy
  • Underused Strategy – The strategies give the impression of box-ticking – doing just enough to meet the demands of external policies and oversight agencies; and often doing that in a hurry – without true internal ownership of, or commitment to, the strategy. 
  • When strategy has been hijacked
  • When strategy is ‘strategic concrete’

Focus on process, not content

The process of trying to create a strategy may be more valuable than the formal deliverables. Value is sought from the informal process deliverables such as: making sense of the past, learning from experience, encouraging dialogue and communication, and making choices 

A hybrid approach to e-government planning will mean a balance between central and local. So, for instance, it could mean that e-government planning is seen as incremental, as participative, as limited in scope: guiding more than dictating. This approach is sometimes referred to as ‘pick- ing a course and steering it’: being adaptable to new constraints and new circumstances as they arise rather than imagining that the strategy is cast in ‘tablets of stone’. 

Sub-Strategic eGovernment Planning 

Given the many constraints to strategic plan- ning, it may be more feasible to plan at what might be termed the ‘sub-strategic’ level. This pares back what planning hopes to achieve until the intention matches what can be achieved in the organization. 

Tactical-Plus eGovernment Planning 

pushing the objectives of an individual e-government system ‘upstream’ to think how it contributes to the overall work of the organization; 

assessing the opportunity costs of going ahead with this particular e-government system rather than others; and/or 

assessing whether there should be com- patibilities between this and other exist- ing or planned systems. 

Chapter 4 Managing Public Data 

CARTA 

Completeness 

Accuracy
Relevance
Timeliness
Appropriate presentation

Prosumption – Where the consumers of public services themselves become producers of their own data often via web-based electronic forms.

What are the Positions to Consider when Managing?

Situation A: Departmental Location 

Situation B: Low-Level Independence 

Situation C: High-Level Independence 

Situation D: Outsourcing 

Outsourcing 

An equal, if not greater drive to outsourcing is to address human resource constraints by accessing staff, skills and ideas that are not available in-house. Other perceived benefits of outsourcing include the provision of a higher quality of service; greater certainty about costs; greater flexibility, especially of labor since it is easier to hire and fire external staff; access to advanced technology; and greater ability to focus management on the core deliverables of the public sector 

Cons

a clash of work cultures and understanding between the public sector client and the private sector sub-contractor; 

a loss of control over the service being provided, with the sub-contractor starting to dictate to a dependent client; 

a loss of core e-government competencies to the sub-contractor, such as controls over security. 

However, in practice, decision making about outsourcing in the public sector has only partly been driven by organizational rationality. It has also been driven by behavioral/political factors (Peled, 2000a). Managers are found to outsource e-government work because they: 

  • have been naive in their assumptions about the benefits that will ensue
  • believe association with such an initiative will be good for their careers 
  • wish to ‘clip the wings’ of the in-house IT unit
  • stand to gain financially thanks to the covert generosity of the sub-contractor

5.2 People

Competencies can be understood in relation to three domains:

Skills, Knowledge, Attitude 

Attitude is changes by appeals to the the rational mind, the political mind, and the heart. 

Greater use of case studies of e-government failure and/or best practice will likely be a move in the right direction (Parrado, 2002). Cases can persuade stake- holders, for instance, of the dangers of ignoring basic systems development prac- tice, or of the importance of understanding the organizational and human context of e-government systems. 

A good hybrid manager will recognize that psychological factors play a role: autonomy, challenge, recognition and the opportunity for career advancement. Direct work content factors are also important, such as training opportunities, flexibility of work schedule and clarity of task specification. 

On a shorter-term basis, responsibility for a personal development plan can be shifted to the employees, and used as part of the annual performance review. 

Plans must be far more than just a critical path; they must include deliverables, resource requirements, and reporting arrangements. Over time, the number of elements that must be planned has grown, typically in response to perceived problems with past projects. What was once just a ‘project plan’ has now been broken down; for example into: a scope management plan, a resource plan, a risk management plan, a procurement plan, a quality plan, a communication plan, a security plan, a change management plan, and a cost management plan.

Which standards should be followed? ISO 9001:2000 

Peer review – a hybrid rather than rational project technique – seems to have a better record, and has now been adopted by a number of governments as a best practice. 

Behavioral Approaches to Project Management 

the rational model fails to fully explain or predict what happens in the public sector. It also fails to fully guide real-world best practice, leading e-government practitioners to criticize PMMs for their inflexibility. Indeed, some who study the realities of projects see the rational approach as potentially guiding worst practice: 

“IT projects die by their own hand. The more they are bound by lists, rules, checks, restrictions, regulations, and so on, the more they drive out the human spirit of creativity, of innovation, of dealing with ambiguity, and of fun. People brought up in technical environments may not see the horror of this kind of approach.”

To plug this gap, and ensure that a more behavioral approach and more behavioral expertise are introduced, some governments are mandating the involvement of senior non-IT officials. The Canadian government, for example, defines a formal requirement on e-government projects for two things (OECD, 2001). First, a project sponsor who is responsible for the business function, and who has solely behavioral-side competencies ( judgment, leadership, communication, organizational awareness). Second, a project leader who is a senior departmental official with, again, largely behavioral-side competencies and only cursory IT management skills at best. Similarly, the UK government’s analysis of e-government project failures concluded with the requirement for projects to have a ‘senior responsible officer’ (CITU, 2000). The officer would be drawn from the business not the IT side of the organization. 

Primary Project Stakeholders

decision makers: those who make major project-related decisions, such as whether or not to proceed with the project

gatekeepers: those who control access to higher authorities

influencers: those who advise decision makers or whom decision makers take note of

end users: those who will directly use the output from the e-government system and/or from the business function it supports

champions: those who will support and muster resources for the project

Smart behavioral players work to break through the rationality barrier to get to the real objectives and values underneath. 

  • by understanding that professional relationships have different bases and require different techniques from those adopted with social relationships
  • by establishing rapport with the other person: looking for common ground 
  • developing on their areas of interest; even mirroring their speech and body language in order to ‘tune in’
  • by active listening that involves really concentrating and asking questions to get to the root of issues, beliefs, problems, needs, and so on 
  • by tailoring communication to the needs of the recipient 

Tailoring your Message 

The sociable ones: The idealistic ones:
  • Be clear and explicit, don’t just imply. 
  • Show me how people will benefit. 
  • Demonstrate immediate and
    practical results. 
  • Show me respect.
  • Engage with my personal values. 
  • Paint pictures and draw analogies
    that have meaning. 
  • Be passionate and engage my
    imagination. 
  • Show how it will contribute to
    the greater good of human kind.
The theoretical ones: The down to earth ones:
  • Show how it fits into the bigger picture. 
  • Ensure the theoretical base is sound. 
  • Appeal to my intellect and imagination. 
  • Be a credible source of information.
  • Be organized and structured. 
  • Be practical and realistic. 
  • Work logically and systematically
    through your analysis. 
  • Offer proof and evidence.

1. Preparation: Getting as much information as possible not just in relation to the topic under discussion but also in relation to the objectives and values of other parties; being clear about one’s own ‘bottom line’. 

2. Initial exchange: Drawing out other individuals and probing with questions to develop a better sense of their objectives and values; weighing up relative bargain- ing powers. 

3. Negotiation: being assertive; using and observing body language; identifying issues that can easily be agreed and issues that are low-cost to one side but high benefit to the other; being creative about what can be traded; exploring 

possible compromises. 

4. Agreement: summarizing the discussion; avoiding/dealing with last minute conditions. 

5. Implementation: setting out a clear schedule of tasks and responsibilities.

The acquisition of negotiating skills and the ability to apply the techniques just described is becoming increasingly integral to e-government project management 

Components of Massachusetts model: 

  • business problem and scope of work: the problem being addressed; the rationale for the e-government project; and the major tasks to be undertaken; 
  • workplan and time schedule: a Gantt chart ‘not intended to be a project log of each and every small detail, but rather a comprehensive plan of tasks, team resources and timelines’
  • management approach and personnel: for both the steering committee and project implementation team; 
  • acceptance criteria and deliverables: the key outputs from the project and criteria that will be used to judge whether or not that output is acceptable
  • task order budget
  • signatures: of all the key ‘business partners’.

Such structures as the above will allow 

  1. early identification of failures 
  2. mechanisms to disperse learning about both success and failure. 

Why should there be so much politicking around e-government? In short, because two pre-conditions of politicking are met. 

First, there are interdependent groups that have different objectives and values. This is clearly the case in public sector organizations. The ‘interdependent but different’ perspective applies to the formal functional divisions within public agencies. 

Second, there are important but scarce resources involved. 

e-Government brings together in large amounts both critical tangible resources – people, money and equipment – and critical intangible resources – information, power and kudos. They therefore form a key locus for organizational politics. 

Techniques of Influence 

Reason: ‘Relies on the presentation of data and information as the basis for a logical argument that supports a request.’ Reason is typically a first choice for influencing a boss or subordinate, and it often relates to a base of expert or information power. 

Friendliness: ‘Depends on the influencee thinking well of the influencer.’ It is often used with co-workers, but may also be used with subordinates and supe- riors. It often relates to a base of personal power. 

Coalition: ‘Mobilizing other people in the organization to support you, and thereby strengthening your request.’ It depends 

Bargaining: Negotiation and exchanging benefits based upon the social norms of obligation and reciprocate. The resources that are traded are very varied but can include assistance, support and information. It often relates to a base of reward power. Assertiveness: Uses continuous reminders via an insistent and forceful manner. It is often used with subordinates and relates to a base of legitimate power. 

Higher authority: ‘Uses the chain of command and outside sources of power to influence the target person.’ This can be the threat or promise of involving the influencee’s boss, or invoking that boss’ own priorities. It can also involve an appeal to higher ethical or cultural values within the organization. It may involve recourse to outside ‘experts’, such as consultants, or to the media. A variation, much found in e-government, is to blame the technology or the data, though this may fall under the heading of manipulation. Its strength relies particularly on affiliation power. 

Sanctions: Influence through the promise of reward or threat of punishments. In its negative form, this may encompass all formal disciplinary procedures up to dis- missal. It may encompass informal actions: blame, bad-mouthing, bullying. It may also encompass the removal of rewards (e.g. transfer, demotion). Sanctions often relate to a base of legitimate or coercive power. 

Manipulation: Influence by controlling the framing of discussions, or the claimed rules for discussion, or the information that is allowing into a negotiation. Part of this process will be the manipulation of the public discussions and public relations that set much of the agenda for government. This type of approach may also include undermining others involved. 

Withdrawal: Influence through disengagement or non-compliance. 

Time and again, middle managers in public sector organizations have good ideas for new or redesigned e-government systems. Yet they cannot get those ideas implemented. They blame their bosses, or the IT staff, or politicians, and so on. In many cases, though, they should blame themselves for failing to recognize their own need for better communication, negotiation and, above all, influencing skills. 

Chapter 6

Emerging Management Issues for eGovernment 

Great care must be taken that measures are valid (i.e. that they do measure what they seek to measure), relevant (i.e. that they measure something on which the employee’s actions have an effect) and valuable (i.e. that they measure what is organizationally important about the job). IT staff behavior will be skewed by performance measurement towards the measured components of the job and away from the non-measured. Only careful selection of indicators will ensure that this skewing is beneficial for the organization. 

Performance management in the public sector 

  • offer career development opportunities, or psychic pay: quasi-financial incentives such as paid time off or new equipment. In some surveys, public servants rate these above money as preferred rewards. 
  • Use group incentives since individual rewards can demotivate other team members, whereas group rewards tend to encourage collaboration.  
  • do not punish occasional mistakes, only chronic poor performance. Use progressive discipline but also use training and peer pressure. 

Three main focal points for performance indicators can be applied to the IS/IT function: 

Input- IT Measures

Output- Information Services

Outcome- Business Process

Measurement of Performance 

In most cases the measurement procedure will be clear within the indicator definition. Three main assessment indicators:

  • Internal subjective: The measures are based on the judgment of internal clients, such as customer satisfaction rating scales. 
  • Internal objective: The measures are based on objective quantification within the organization, such as the jobseeker placement measure. 
  • External: The measures are based on quantification from outside the organization. 
  • Price testing: Comparing the internal costs of a service with the estimated cost/price of external providers and benchmarking (which includes a broader set of performance measures) 

Control of Performance 

Provider management control: Managers within the IS/IT service provider are responsible for managerial rewards and remedial measures. 

Client management control: Managers within the IS/IT service client are responsible for managerial rewards and remedial measures. 

Client financial control: Managers within the IS/IT service client are responsible for financial rewards and remedial measures. 

Arbitrary basis: The sum paid does not relate to service use but to some relatively arbitrary measure such as the size of the user department. The lack of linkage creates limited financial control on performance; arguably less than that available via a managed service level agreement. 

Cost basis

Market basis 

The central thrust is that agencies must be good at writing documents and at managing projects. It would thus be possible to score a ‘green’ without producing anything that had actually made life better for citizens and other agency clients. 

The more the government charges for its data, the greater the barriers to access become. Yet the wider it allows access, the less it can earn from data sales. 

Access Policies for Freedom of Information

The enactment of FOI legislation has required the development of in-house policies by public agencies within its purview. Typical issues to be dealt with include (DOI, 2002): 

Terminology: Explicitly defining what is meant by terms such as records and requests; and classification of different types of data held by the agency.

Procedures: Clarifying how citizens/ businesses can obtain data direct without requests; how information requests are to be made; and the means by which those requests will be responded to.

Data management: Ensuring that the type of back-office, records and data manage- ment procedures described elsewhere in this chapter are followed so that data and records can be located in a timely and cost-efficient manner.

Performance measures: Setting out performance indicators (typically time taken) for the FOI response service.

Charges: Determining a reasonable level of charges to be levied for searches and copying; determining policy on any fee waivers; putting a billing and payment system in place.

Handling variations: Determining procedures in the case of various types of data/records such as those not held by the agency; those held by other public agencies; those deemed sensitive or covered by privacy legislation; those held by other non-public agencies.

Appeals: Setting in place an appeals procedure to appeal against problems with performance, charges or denial of access.

Responsibilities: Designating specific officers as responsible for FOI implementation, and for appeals. 

Update: Putting in place a mechanism for review and update of FOI procedures (e.g. in response to new technology, case law, organizational changes, new orders, or FOI response performance and feedback). 

Digital Divide

Because of those costs, there is an uneven profile of those who own and use IT: the rich not the poor; the graduate not the school leaver; the ethnic majority not the ethnic minority; the urban not the rural citizen; the young not the old; men not women. 

Pouring resources into e-government can therefore benefit the haves rather than have nots, and increase polarization within society. There are already some signs of this, with evidence that local government electronic service delivery is of poorer quality in areas with lower levels of Internet access 

Governments may set up initiatives focused on increasing access to IT that is government-or-community-owned IT. Such IT may be placed in a variety of locations: 

  • public spaces, such as common areas within shopping malls; 
  • semi-public spaces, such as libraries or sport facilities; 
  • dedicated spaces, such as community telecentres housing a room-full of Internet- linked PCs. 

The watch- word for government must therefore be ‘supplement’ not ‘supplant’. Provision of public sector data and other services electronically should be seen as an additional weapon in the armory that sits alongside traditional face-to-face and phone-based methods. It should not be seen as a way of replacing those more traditional methods. 

Reviewing Sensitive Public Information

The following questions will assist security professionals in reviewing sensitive infor- mation that has been, or could be, made publicly accessible. 

Has the information been cleared and authorized for public release?

What impact could the information have if it was inadvertently transferred to an
unintended audience?

Does the information provide details concerning enterprise security?

Does the information contain personnel information such as biographical data,
addresses, etc.?

How could someone intent on causing harm misuse the information?

What instructions should be given to legitimate custodians of sensitive information
with regard to disseminating the information to other parties such as contractors?

Could this information be dangerous if it were used in conjunction with other
publicly available information?

Could someone use the information to target personnel, facilities or operations? 

Could the same or similar information be found elsewhere?

Does the information increase the attractiveness of a target? (OCIPEP, 2002)

Policies on Disability

the law sets a clear threshold that must be achieved. However, in practice, e-government managers often seem to be ‘satisficing’ the issue: doing just enough to cover their backs but still leaving a gap between policy and practice.

Difficulties

public managers face a difficult balancing act between the requirements of central legislation and the localized needs of the public agency. These may conflict where, for example, the agency has to make the best of an outdated physical environ- ment, or where lack of money means what is ergonomically-best cannot be afforded. This balancing act can appear in the gap between policy on paper and policy in prac- tice. eGovernment managers may develop an internal policy document that fully meets all legislative requirements, but may then not fully implement the document. 

Chapter 7

Success in e-government comes from intelligent selection of individual techniques, from
‘hybrid thinking’, and from action on design–reality gaps rather than from slavish adherence to one particular methodology.

Background understanding of a proposed e-government project comes from asking five
questions: Who is involved? What is the problem? Why is the project happening? What
constraints exist? What will change in the near future?

eGovernment projects can be assessed in relation to their feasibility, priority, opportunity costs, and impact.

Four Core Stages:

1. analysis of what is currently happening, and of whether and why a new e-government system is needed
2. design of the new e-government system’s components
3. construction of the new e-government system

4. implementation of the new e-government system 

Successfully planned e-government systems will therefore be those that require a manageable degree of change. 

In order to assess this ‘degree of change’, the core of the systems development method described here will therefore consist of three activities: 

  1. mapping out the realities of the current situation
  2. designing a proposal for the new situation
  3. assessing the difference between the two, and reacting to that difference 

Systems Development Life Cycle

1. Project assessment: Identifying possible e-government projects; outlining basic project parameters; and assessing whether or not to proceed with the project. 

2. Analysis of current reality: Description and analysis of the seven ITPOSMO dimensions as they exist within the current situation of the organization. 

3. Design of the proposed new situation: Setting objectives for the proposed new e-government system, and then describing in general terms how the seven ITPOSMO dimensions should be different for the new system to meet these objectives. Different options for the new system may be evaluated at this point. 

4. System construction: Acquiring any new technology; undertaking detailed design of the new system; then building it, testing it and documenting it. 

5. Implementation and beyond: Training users to use the new system; converting data to new formats; introducing the new system; monitoring and evaluating its performance and context; then undertaking any necessary system maintenance. 

SSADM: Structured Systems Analysis and Design Methodology, 

No method is perfect but there are dangers for the public sector in adopting some of the harder methods. The public sector has had a tendency to choose such methods which then prove too old, inflexible, top-down, detailed, jargonized and time-consuming (Korac-Boisvert and Kouzmin, 1995). While these might have been appropriate to the routine clerical automations of the 1960s, they work poorly in politicized situations of change and uncertainty. 

 

Review of Democratic Process and Digital Platforms: An Engineering Perspective

Democratic Process and Digital Platforms: An Engineering Perspective by Danilo Pianini and Andrea Omicini is a book chapter published in The Future of Digital Democracy by Springer in 2019. 

Over the last decade, many 4th Industrial Revolution tools and platforms have emerged which contributed to the expanded capabilities adoption of digital democracy. Many countries, in fact, are now creating government ministries in charge of determining how they can be adopted. Because of various social and political pressures as well as the incredibly complex and multi-disciplinary nature of research and development related to digital democracy platforms, several fundamental concerns still remain unanswered. In this book chapter Danilo Pianini and Andrea Omicini focus on those issues that are more traditionally conceived of as relating to the engineering process. 

In the analysis phase of the classic software engineering process, one or more artifacts are produced that represent a formal model of the domain. 

Looking at two e-democracy platforms adopted by electoral parties, the authors show that this imperative step is missing, along with other phases of engineering process development. Their chapter relates evidence about the current status of digital democracy using several case studies – in platforms such as Rousseau and Liquid Feedback, and then reviews the primary software engineering issues that future tool and platform developers should consider when determining how to improve existent digital democracy software. 

Definitions

Citing Joseph Schumpeter in Capitalism, Socialism and Democracy, the authors defer to his classic definition of democracy as the “institutional arrangement for arriving at political decisions in which individuals acquire the power to decide by means of a competitive struggle for the people’s vote.” While silent on accountability of rulers, how political proposals are defined, who can vote, how votes are tallied and contextualized (i.e. via their relationship to legal institutions such as the Electoral College), etc. the concern of democracy is clearly on legitimizing power. 

Given the numerous ways that citizen-stakeholders can now include software in such processes and the increased diffusion of technology – the authors state that a new form of democracy, digital democracy, is increasingly influencing the techno-political landscape and forcing the evolution of our understanding of the possible within politics. 

While there are numerous varieties of functional differentiation which exists between digital democracy platforms, the authors identify four fundamental phases common to each:

  1. Preparation of the proposal.
  2. Expression of users opinions.
  3. Summarization of the opinions into a decision.
  4. Enactment of the decision. 

Pirate Party’s Liquid Feedback and the Dictatorship of the Active Ones

Several non-traditional parties, going by the name of the Pirate Party, have emerged in Europe over the past several years. The administrative and managerial elements within these political parties adopted Liquid Feedback as a means of facilitating policy formulation. 

One of the problems with this particular platform, however, was the lack of limitations that were placed on discursive participation that subsequently gave rise to the phrase “Dictatorship of the Active Ones.” The model of democracy implicit within the platform sought to maximize expressive capacity via what was, essentially, a complex message board. A problem with this format, however, meant that users who produced large quantities of input and commentary could potentially down out users that were shared less, but of higher quality. It’s likely that because of this issue which caused the platform to be abandoned.

Reverse-Engineering Italy’s Rousseau 

Jean Jacques Rousseau deemed that the ideal form of government was that which was administered by the General Will. Fitting, then, that one of the digital democracy platforms, adopted in Italy by Movimiento 5 Stelle (5 Star Movement), would be named after him. 

Unlike Liquid Feedback there is significantly more capacity for the administrators of the platform to control proposal submission and debate on it. The above diagram shows a reverse-engineered description how it is that the platform worked.

A few democratic issues the authors note the Rousseau platform has are: 

  • Lack of enacting mechanisms for the user proposals
  • Opaque user proposal selection process
  • Chaotic proposal organization
  • Lack of comment moderation on law proposal
  • Unclear impact of comments on law proposals

What is to be done?: Determine How Best to Operationalize Democratic Processes

After the author’s have assessed Liquid Feedback and Rousseau, they point to two major issues in their deployment. First, the evident lack of appropriate software engineering processes applied to development of the platforms and, secondly, the lack of research on modern democratic processes that would allow for the porting of a model of democracy.

On the first point the authors claim that were the designers of these egovernment platforms to have approached the project from a holistic perspective rather than that which sought merely to digitize a few democratic processes then they would have used a waterfall software engineering process. Composed of a sequence of phases that lead from the idea to the implementation, the waterfall software engineering phase takes this order: 

– definition of the requirements 
– analysis
– architectural design
– detailed design 
– verification 
– implementation 
– maintenance 

On the second point the authors claim that this model was avoided due to the difficulty of defining the requirements to adequately operationalize democratic processes. In their own words, they state that: 

“Part of the problem depends on to the orthogonality of the matter: in fact, it requires understanding and expertise over an extremely diverse number of subjects, spanning from humanities to applied sciences through social and natural sciences—including, but not limited to, sociology, psychology, law, mathematics, engineering, and computer science. It is then unlikely for small teams to possess and master such a wide expertise, and – along with the typical lack of interdisciplinary cross collaborations – this makes defining/refining knowledge on democratic processes, and their formalisation as well, a difficult issue indeed.” (92)

As digital democracy platforms, in effect, create their own democracy process rather than match what already exists in law – to produce a platform at a whole of government level rather than that which allows for idea solicitation and feedback from parties requires extensive research and development.

Concluding Thoughts 

To say that digital democracy is the future and that it will have revolutionary impacts on governance and accountability is an understatement. However to achieve this requires further investment in the creation of a model of democracy that is widely agreed upon in order to develop the functional requirements of the platform. 

To work the other way around, the authors contend, is neither a scientific, engineering-minded approach to the matter a hand nor one that allows for optimal operationalization of democracy via digital technology. Give the novelty of much of this research – what is needed is “a strongly-multidisciplinary effort: [as] currently, many issues remain open, and many key questions are still unanswered.” (93).  

Though the authors of this article focus solely on the Waterfall process, I think that it’s worth mentioning in an aside that was there to be actual government investment into the project rather than just the parties running for the positions within it, it would be possible to use an Agile model for the development of an egovernment platform. In this case, the sequencing of phases in an Agile model would look like this (Managing Software Process Evolution):

Given current levels of political polarization and typically low level of technical knowledge of elected politicians it is likely that this would be a very difficult process. It is, nevertheless, within the realm of possibility.

Citations

Managing Software Process Evolution: Traditional, Agile and Beyond – How to Handle Process Change edited by Marco Kuhrmann, Jürgen Münch, Ita Richardson, Andreas Rausch, He Zhang

Keywords: Digital democracy · Software engineering · Democratic model 

English Translation of Techno-Science as a Political Space

Originally written by Xabier Barandiaran

        xabier@barandiaran.net
        http://barandiaran.net

for Autonomía Situada

http://sindominio.net/autonomiasituada

Summary

Technoscience has become the main source of power (productive and structural) in the knowledge society. At the same time, the main source of funding for technoscientific processes, public investment, is mainly oriented towards innovation within the framework of the market economy and war and progressive restriction of the free circulation of knowledge and techniques. In this context we present the project Autonomy Located as a space for research, production, diffusion and collective learning around cybernetics, artificial life and cognitive sciences.

Keywords

Technoscience, knowledge society, philosophy of science, techno-scientific policy, collective research, autonomy and social self-organization, cognitive sciences, cybernetics, artificial life, Situated Autonomy.

1. Introduction

This document is an elaboration of the presentation speech of Situated Autonomy that took place at the Copyleft Conference during the days 27-30 of March 2003 in The Laboratory 03 and La Casa Encendida, Lavapiés, Madrid.

Unfortunately, we did not have enough time for the presentation to be the result of the collective work carried out on the Gray-Walter1 list (virtual assembly of the group), so this document does not respond to the collectively elaborated and consensus based reflection on the common work we have done. come doing. However, I hope to have been faithful to the analysis, orientation and expectations that we have built during the barely six months of our journey.

This document is divided into two fundamental parts, in the first of them (sections 2 and 3) I describe the context of techno-scientific policy on which the figure of the Situated Autonomy project is drawn, a context that serves as a political and cognitive contrast in which The outline of our project is drawn with the importance and urgency that we believe it has. The second part (section 4) makes a presentation of the work done so far, the motivation that pushed us to create the group, and the future expectations we have as well as the general lines of our organization of techno-cognitive work.

Before starting I would like to advance a brief presentation of what is Autonomy Situated. 

Located Autonomy is a project and a community of learning, dissemination and research on cybernetics, artificial life and cognitive sciences. Because it seeks to generate and disseminate knowledge (and its derived technology) in a self-organized, horizontal and participatory manner it is an autonomous project. We also consider that ours is a situated project because we seek to re-situate the processes of production, learning and techno-scientific diffusion in the social reality that surrounds us in the face of academic, corporate and military research. Our goal is to create a techno-scientific space on the idea of the open cognitive code, free dissemination and participation and collective intelligence, breaking the boundaries between processes of production, use and dissemination of scientific knowledge (an Independent Research Center). Cybernetics, artificial life and cognitive sciences have an unexplored potential to serve as a theoretical and technological framework for new forms of self-organization of cognitive and social processes; at the same time, they discover the systemic and computational foundations that define life, information, mind and networks (social, communicative and electronic).

2 The knowledge society: A Society of Risk

In this section I would like to make a brief review and some possible redefinitions of the labels that are being used to define the space and time we live, such as technoscience, information society, knowledge society, risk society, etc. As they did well to point out, the psychologists of Gestalt background and figure require each other to make the perception of an object emerge. In the same way, I would now like to dedicate a few minutes to defining the specific context on which to properly cut the significance of our project.

2.1 The knowledge society

The fact that we live in an information society and a knowledge society is now commonplace. However, it is necessary to make a series of distinctions and a review of the defining characteristics of the knowledge society in order to progressively focus on the modes of organization of techno-scientific processes and their political relevance.

The digital age allows the manipulation, storage, distribution and copying of digitized signals. A digital universe, unprecedented in the history of humanity, is produced through the codification and recoding of signals. However, it is worth remembering that isolated digitalization is not a differential fact of our societies, nor is the fact of the predominance of information as a social product. It is rather knowledge (and especially scientific knowledge) and its effects on production and social organization, which makes it possible to claim a difference between our society and its precedents. Digitization and information technologies are enabling conditions for a knowledge society, conditions that are effectively necessary, but not sufficient.

It is convenient at this point to clarify (through a series of definitions) the dependence relations between digitization, information, knowledge, technique, technology and technoscience:

Digitization:

process that imposes a separation of the continuous (the analogous), giving rise to a discretization and coding that allows building a computationally manipulable world.

Information:

signals or registers of more or less ordered signals susceptible of interpretation by an intelligent system to produce knowledge.

Knowledge:

set of skills and functional information organization that allow effective action on a domain of the real.

Technique:

practical application of knowledge.

Technology:

sphere of the real produced by the recursive application of the technique.

Technoscience:

process in which science and technology are strongly embedded in mutual feedback: science allows the development of new technologies that in turn accelerate or influence the scientific process, which in turn allows new technologies …

What really defines current societies is that cognitive processes (especially those of a scientific nature) applied to the production and organization of production processes, to the forms of social organization and to the resolution of conflicts, become the main factor of increase in the productive force and in processes of constitution of society itself, thus placing itself as primary sources of power (structural and productive). To this must be added the irruption of communication and information technologies that allow a flow, copy, storage and management of information (and therefore of codifiable knowledge) that in turn accelerates knowledge production processes. This is what marks a qualitative change in the forms of production that characterize our societies against their historical precedents: a technological reflexivity about knowledge.

This knowledge society is marked by a series of features that we can pick up in the following enumeration:

The greatest factor in increasing the productive force is techno-scientific innovation, thus producing a dematerialization of the economy in which technoscience is the first productive force (centers of innovation, consultancies, exchange and information management, quality controls, etc.). The difference between the production capacity of different societies no longer resides so much in the amount of material resources and accumulated resources but in cognitive processes (especially those of a scientific nature) and their recursive application on reality (material and social): technology.

The digital technologies of information and communication reinforce this trend by allowing the reproduction, dissemination, storage and management of information and knowledge.

The recursive application of technoscientific products on production processes reinforces the trend.

This is made evident via the facts that:

  • A greater proportion of the intangible production is observed in the GDP and in the employment rate (cognitive).
  • Greater weight of science and technology in public management and public decision-making (in the form of technical advice).
  • Greater public investment in techno-scientific and innovation processes.
  • Increased presence of the need for technological skills and knowledge (as well as local information – about the choice of purchases, of day-to-day decisions) in daily life, as opposed to respect for traditional ways, correction according to institutions symbolic-religious, which characterized daily life in ancient society.

It can be argued that all societies have been knowledge societies in some way but in our case it is that scientific knowledge and its management is the fundamental source of power (productive and structural), and thus becomes a constituent element of the society itself. Habermas (1968) goes so far as to affirm that the real qualitative change of modern societies is that the ends-means rationality (whose maximum expression is technoscience) becomes the legitimating foundation of political domination. But we’ll talk about this later. Let us focus first on the forms that the organization acquires of these technoscientific processes constitutive of our knowledge societies.

2.2 The Risk Society

The “other face” of techno-scientific development has been revealed under another label that has also become common currency to designate our societies: “The risk society”. Popularized by Beck (1986) in his work of the same title, the risk society points to the catastrophic consequences and social, psychological, medical, environmental and other dangers that products and techno-scientific interventions produce. The theme of risk thus becomes one of the main sources of politicization of the techno-scientific process.

Beck characterizes the risk society based on three fundamental features:

  1. Many of the risks of today’s society are of a catastrophic nature derived from techno-scientific products: explosions, major accidents, or larval catastrophes (destruction of the forest, acid rain, etc.). These catastrophes and risks do not respect borders (neither of species, nor of nations, nor of social, nor generational classes, etc.). The traditional risks were limited to certain conditions, classes, nations. The new risks are global.
  1. Risk is present in the center of everyday life, in the sense that we constantly have to make risky decisions such as consumers, parents, bus drivers, etc. There is a lack of a binding tradition in individual conduct that requires permanent decisions on equally permanent risks. Previously decisions related to consumption were dictated by the tradition and technologies were adjusted to over years of presence and sedimentation.
  1. These risks are not experienced as inevitable damages (dangers) but as risks. The difference between risk and danger is that the risk is subject to attribution of responsibilities (unlike an earthquake, hurricane, etc.). But even natural catastrophes are conceptualized as risks (at least their effects) since we have enough technology to neutralize damage, although the cause of it is inevitable. The more science and technology there are, the dangers become risks thanks to their possible preventability.

The paradox of knowledge societies are shown in the risks generated: more knowledge and technology plus risk, both because of the possibility of avoiding hazards and because of the technologically generated risks. The new devices (electronic, nuclear, chemical, biological, etc.) introduced into the market and production processes have often unpredictable impacts on society, health and the environment. Part of the public policy in science and technology (as we saw in the previous section) is aimed at alleviating these adverse effects. But if we keep Bush’s linear model of a polarization between laboratory and society, a polarization that is mediated by commercialization, the regulation of interfaces will barely avoid some of the predictably most scandalous impacts.

2.2.1 Post-normal science and values in science

In this context, techno-scientific spaces that escape the traditional classifications of “normal” scientific work are shown to work with indefinite terms, low uncertainty, based on well-established research traditions, etc. Under the name of postnormal science Funtowicz and Ravetz (1990) have detected and analyzed techno-scientific spaces of high uncertainty, with great potential for impact and aimed at solving problems of great complexity in very limited periods. Techno-scientific practices that take place in many sectors of industry, in the control of nuclear power plants and techno-scientific super devices, evaluation of environmental risks, biotechnologies, pharmaceutical laboratories, etc. The practice of post-normal science is discovered loaded with values in the forms of measurement and evaluation: correction of errors, statistical measurements, analysis of damages, etc. (López Cerezo and Luján, 2001). Scientists working in post-normal science have to respond to various interests and pressures, in limited time frames and face having to make urgent decisions with uncertain consequences. And this trend is not an isolated case but a generalized practice that discovers a large part of the techno-scientific practice (if not all) crossed by values (Echeverría, 2001).

3 Techno-scientific policy, politics in technoscience and technoscience as politics

In the framework of what we have been saying, the form taken by the evaluation, regulation and financing of techno-scientific processes is shown as a fundamental structure with which to reflect on society itself, especially in the way in which public investment (the majority ) in science and technology defines the nature of this process. In this section we will make a brief history of the relationship between the techno-scientific process and its evaluation and public regulation, while we review the indicators that public institutions have used to develop their work.

3.1 Public policy in the organization of technoscientific processes

The inherited conception of science that comes from the logical positivism of the 1930s draws a science guided by purely epistemic values (of rationality, rigor, logical consistency, contrastability, publicity, and intersubjectivity) and autonomous (ie not marked by interests external to the scientific practice) that are those that supposedly mark and ensure the excellence of science and its results. It was considered therefore that science was a self-regulated and disinterested practice.

Within the framework of this interpretation of science and after the Second World War (and the fundamental role that science and technology played in it), the Bush Report (1945) was drafted, whose title “Science, the Endless Frontier” already condenses optimism and confidence in the possibilities of scientific development. The Vannevar Bush report of 1945 marked US scientific policy, which would soon spread to the rest of the developed countries including the communists. In the words of the author:

Advances in science when put to practical use mean more jobs, higher wages, shorter hours, more abundant crops, more leisure for recreation, for study, for learning how to live without the deadening drudgery which is the burden of the common man for ages past. But to achieve these objectives … the flow of new scientific knowledge must be both continuous and substantial.

(Bush, 1945, p.5), taken from (Sarewitz, 1996, p.17)

The image of an autonomous and self-regulated science from which social benefits inevitably followed gave rise to a scientific policy of “ laissez faire ” (letting science do it) to which resources had to be provided unconditionally in the form of a blank check, to ensure input to a process from which an invisible hand was expected to distribute the product in the form of social benefit. Thus, a linear model of organization of the techno-scientific process (which lasts until today) is established under the structure illustrated in figure 1.

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More input to science amounted, then, to more social welfare, so that scientific policy only had to ensure a series of almost unlimited resources, thus establishing the social justification of science and public investment in it. This first stage of relations between the governmental public sphere and techno-scientific processes is marked by the first generation indicators, which are basically input indicators, which measure the total expenditure on science and technology and the number of human resources in the sector.

It will not be until the end of the 1950s that Western countries begin to consider a more active scientific policy with the launching of Sputnik and the demonstration of techno-scientific superiority of the Soviet Union. This is how, even without abandoning the linear model, the US could consider a relative control of scientific education and a process of evaluation of techno-scientific production to ensure its quality. Specialized academic institutions, institutes of science studies were created and curricular programs were revised. The characteristic indicators of this stage are the Frascati indicators that are output indicators to evaluate the efficiency of the scientific-technological production process, measured through: the number of published articles and citations (science index citation) for science and number of patents for the technological production process. The idea of a self-regulated science is broken in a certain way, since by more input it is no longer considered that there is necessarily more production output and the process must be controlled and its efficiency maximized, but the linear model that is now being optimized is maintained.

We will have to wait until the end of the 60’s and the beginning of the 70’s to begin to see a concern (and the consequent institutional efforts) to regulate the technoscientific products. It was in the wake of the student protests of ’68, the anti-nuclear movement and environmental movements (including those concerned about public health), that a public awareness of the risks inherent in a growing transformation of the world by technoscientific interventions and products began to be generated. Thus emerged the EPA (Environmental Protection Agency), the OTA (Office of Technology Assessment) and other government institutions aimed at assessing and regulating the effects and risks arising from the techno-scientific production. At the same time the inherited conception of science begins to fall and a vision of science begins to take shape (championed by the Khunian perspective of “The structure of scientific revolutions”) in which the discontinuities of scientific progress are shown as well as its dependencies of social and historical contexts. Evaluation and regulation mechanisms were established to reduce the negative effects, optimize the positive effects and contribute to the public acceptance of given technologies. The types of impact of techno-scientific products (environmental, psychological, institutional, social, legal, economic, etc.) are identified, analyzed (their probability, affected groups, response of these, etc.), assessed (assumable risks, etc.) and advice is sought for decision making on techno-scientific policy. Longer term evaluations that introduce side effects are also beginning to be established. But this is still a kind of “let the technology continue to develop and correct the adverse side impacts it may have”. It is a type of scientific evaluation (involving almost exclusively scientists and technicians) that is reactive (focused only on the evaluation of products that are about to be released to the market) and almost exclusively economic and probabilistic orientation (with type indicators aligned with cost / benefit analysis).

In a final stage of this generalist history of the evolution of public policy in science and technology, the concept of innovation begins to predominate. Based on the two dimensions of the concept of innovation, which are the techno-scientific novelty and the benefit derived from its introduction into the market, it is now a matter of intervening in the techno-scientific process to maximize its economic performance. It seeks to optimize the fit between science, technology, business and market. Public investment begins to be directed towards the creation of techno-scientific transfer centers from universities to companies, resource management offices, etc. to maximize the innovation process. Of particular concern is the absence of society as an environment for adjustment, and the paradoxical situation arises that the first techno-scientific regulation efforts achieved by social movements aimed at alleviating their environmental, health and social effects are now redirected towards the maximization of their economic performance. In the words of Dickson (1988): “Where new technological projects have previously been studied for their environmental impact, the regulations are presented to mitigate this impact, in reverse, have to be evaluated for their economic impact.”2 ( p.311). The innovation indicators characteristic of this stage appear in the 80s and are consolidated in the 1990s as a consensus set of innovation indicators (in the Oslo manual). These indicators are mainly surveys to entrepreneurs to measure the level of exploitation in the market of scientific discoveries. This is a substantial change because an impact of improvement in the market derived from scientific policy is requested. It has gone from the science-push (in the Bush model, in which resources are introduced in science and scientific processes are expected to “self-regulate”) to market-pull (in which the market marks the lines of research and innovation). To the extent of the number of patents and scientific articles published to give approval to research projects, consultancies are now added to companies and DCRs (restricted circulation documents, restricted use studies oriented to technological and innovation companies).

3.1.1 Techno-scientific organization

Summing up what we have been saying we find an organization of techno-scientific processes articulated under four fundamental types of techno-scientific work:

Basic science: research is, in principle, not subject to practical interests and seeks to expand the limits of scientific knowledge (physics, chemistry, biology, etc.).

Applied science: research guided by the interest in solving technical problems in the field of science and technology.

Technology: aimed at the production of artifacts and mechanisms based on established scientific knowledge.

Postnormal science: scientific practices carried out under a high degree of uncertainty and great potential for impact.

Finally, the mutual and recurrent interactions between them can be collected under the concept of technoscience, which is mainly oriented towards:

Military research in programs of the international scientific vanguard, generally marked by power groups and Western scientific traditions (to which about 54% of public investment in science and technology is devoted in the US).

The market: biotechnology, pharmaceutical, research into new materials, etc.

evaluated, regulated and financed based on:

  • its performance in the market and innovation processes
  • its possible impact on public health and the environment
  • its production measured based on internal standards (such as the number of published articles and adaptation to research lines) of scientific power groups that have grown up around research traditions.

3.2 Myths: ideology in technoscience

In “Frontiers of illusion: Science, Technology and the Politics of Progress” Daniel Sarewitz dismantles the socially and politically constructed mythology that sustains Bush’s linear model, the ethical and political autonomy of scientific practice, the assumption of the necessary benefit of techno-scientific research and development and hope put in science as an authority for the resolution of political problems. According to this author throughout the last decades, a social narrative of techno-scientific determinism has been built, driven by: 

  1. the power groups of scientific and academic institutions (to justify and increase public investment in their research traditions) 
  2. corporations and the market based on innovation (to allow them to continue to benefit from and take ownership of public investment and collective cognitive production) and c) finally by politicians themselves who succumb to the temptation to substitute institutional political commitment for the techno-scientific rationality.

While this narrative is maintained we are condemned to a techno-scientific process that progressively moves away from the social benefit that it could produce (and that paradoxically aims to legitimize public policy in science and technology). A distancing accentuated by two trends:

Placing technoscience in a context of market adjustment (as recent public policies in R & D and innovation suggest and enhance) has two fundamental consequences:

the tendency for society to assimilate techno-scientific products through the independent social welfare market that they can produce (sometimes even against social welfare) is favored

the tendency is favored that the techno-scientific production ends up preferentially oriented towards the classes with greater purchasing power, which are, in short, those with the greatest potential for consumption and, paradoxically, those with the least social problems. The political agenda of R & D moves away, thus, progressively from the most urgent social problems.

In this way and in the words of Sarewitz “ Science and technology are facing an economic task that is inherently sisífea: increase the human need to consume. ” (Sarewitz, 1996, p.128).

Moreover, the myths on which scientific policy is based surpass its function as a legitimizing discourse of current techno-scientific practice, underpinning confidence in a market economy based on innovation; i.e. They feed the confidence necessary for the deployment of capitalism in knowledge societies.

Substitute social policy for techno-scientific policy. In a whole chapter devoted to the topic, Sarewitz shows how it tends progressively to replace institutional interventions and political decisions aimed at social change through public policies in support of techno-scientific production: subsidies to pharmaceutical companies to solve physical and mental health problems, to biotechnology to solve hunger problems, and a long etc. In addition, the belief that more research will solve certain social problems is subject to a debate infinitely less than other types of political budgets.

Regarding the discourse that considers science as a development factor for third world countries, the paradox shows that the interest of academic science (to which third world scientists must adhere) is marked by large scientific publishers whose interests respond to the research programs of the northern countries. So scientists from developing countries work for the first world, that is the one that marks the scientific directives, which in turn are regulated by organizations that seek to maximize the innovation of their own country. In this way, developed countries appropriate the scientific processes of developing countries to maximize their innovation.

3.3 Alternatives: constructive evaluation and public participation

Faced with the difficulties and trends mentioned, critical voices and participatory proposals have been developed. Among them stands out the model of constructive evaluation of the technologies developed by Rip and collaborators (1995) whose main hypotheses (oriented to overcome the techno-scientific deterministic model) are that:

Technological development results from a large number of decisions made by different heterogeneous actors. In the negotiation of technical options, the diversity of centers and decision criteria implies a certain degree of technical plasticity. The various agents involved shape the techno-scientific development with what breaks the linear model and the associated techno-scientific determinism.

The technological options can not be reduced to its strictly technical dimension. Hence, the evaluation of technological options is a topic of political debate.

Technological decisions produce irreversible situations, which result from the gradual disappearance of the available margins of choice.

The practical horizon is to redirect the processes of innovation and development towards socially transparent processes:

where a multiplicity of actors can have a presence,

where a variety of analysis tools and values are used, and

where social learning can take place.

The focus of regulation is on emerging technologies (as opposed to finished products), the function is that of an early warning (rather than a containment of the product) and the basis of regulation is the knowledge of the dynamics of technology and the role of social agents in the modulation of innovation.

This approach considers that through the coevolution of technology and society the problems of anticipating the technoscientific effects on society and the environment can be solved and the deterministic techno-scientific model can be broken. To the extent that we can intervene in the selection agents, there is no longer a problem of anticipation because there is nothing to anticipate but something to build. This approach is about opening participation to the processes of selection of technologies.

At the same time, models of public participation are being developed in an attempt to democratize techno-scientific construction:

  • seeking to open decision-making in science and technology policies with various models such as citizen panels * s, referendums, consensus-oriented participatory conferences, citizenship advisory committees * s, working groups, etc.
  • promoting the promotion of education policies in scientific culture that include the awareness of the value, ethical and political burden of techno-scientific practice
  • seeking to reorient the public policies of science and technology towards the most urgent, local social problems in the most neglected spaces.

Proof these types of initiatives are already in progress are shown in the so-called “Science Shop” that, despite its name, condense some of the most important proposals of public participation. The idea is to create windows to the society that allow to offer the knowledge generated in the university to groups without resources so that they can take advantage of them. It is also sought that the university (through the science shop) mediates techno-scientific conflicts, as well as letting information from society to the university, making the university itself can meet the needs of society.

Without taking away the relevance, urgency and priority that this type of initiative deserves, one can question the current model further and draw more radical perspectives of transformation (at least in some specific aspects of techno-scientific development); but first, it is necessary to pay some attention to the process of commodification that technoscience and restrictive forces (in terms of the dissemination and transformation of knowledge) that this process generates are undergoing.

3.4 Intellectual property & Commercialization of Knowledge and Techniques

“The sudden and unbridled passion for private property in the field of knowledge has created a paradoxical situation. While the technological conditions (coding and transmission at a reduced cost) are given so that everyone can benefit from immediate and perfect access to new knowledge, the increasing number of intellectual property rights prohibits access to this knowledge in areas that until then had been preserved (fundamental research in general, biological science, computer programs). An attempt is made to create an artificial rarity in a sphere in which abundance is the natural rule. This causes huge waste.”

(David and Foray, 2001, p.15)

“Indeed, we are faced with a growing commercialization of cognitive products that is especially aggravating in the context of publicly subsidized research, in which more and more new public policies aimed at innovation are required, patentable results and / or subjects to copyright. A dynamic in which the university world is not an exception, but a standard-bearer in this trend.” (González-Barahona, 2003).

If the traditional tendency in science was to gain recognition in the scientific community for the quality of the research, Etzkowitz and Webster (1995) show that the credibility in science is now progressively linked to the ability to generate economically exploitable knowledge.

As these authors point out, what is important, in the process of capitalization of the science that we live, is no longer the authorship of a relevant research, but to ensure intellectual property, its exploitation in the market and the ability to acquire added value. To ensure the viability of this process, it is fundamental to restrict the free dissemination, copying and transformation of knowledge and techniques through the force of the law embodied in patent and copyright legislation. That is, in the techno-scientific economy, intellectual authorship becomes the right to exploit a knowledge or technique through the restriction of dissemination, use and transformation of the product, even when the production process is financed by public investment and mobilizes infinity of collective cognitive resources (universities, inherited knowledge, collective research projects and instruments and techniques that belong to the public domain). Something already advanced by Lyotard (1979) apropos of the digitized externalization of knowledge:

The relationships between the suppliers and users of knowledge to the knowledge they supply and use are now tending, and will increasingly tend to take the form taken by the commodity producers and consumers to the commodities they produce and consume – that is, the form of value. Knowledge is and will be produced in order to be sold, it is and will be consumed in order to be valued in a new production: in both cases, the goal is exchange.4

(Lyotard, 1979, §1)

In this context, the social re-appropriation of techno-scientific production requires demanding policies for the liberation of knowledge, its free access, use, dissemination and modification. This requirement and practice is being articulated by the copyleft community in the fields of art, science, technology, and literature. This heterogeneous community of actors, producers, consumers and disseminators of knowledge uses the various copyleft licenses (built on copyright legislation5) meticulously designed to build and defend a legal territory on which to build cognitive communities of free distribution, transformation and appropriation of cognitive and technical work.

The advantages of a release of cognitive production through copyleft licenses have been underlined again and again, but it is nevertheless necessary to briefly collect some of the most important arguments in this regard:

  • Freedom of access, dissemination and transformation.
  • Gradual improvement of the material thanks to the right (recursive) of product handling.
  • Techno-cognitive diversity thanks to the multiple elaborations of the same product.
  • Disappearance of intermediaries in the diffusion guided by the direct benefit extracted from the product and not by the quality of it.
  • Survival in the ecosystem of attention in which copyright as a copy restriction supposes a memetic suicide. (Cervera, 2003).
  • Revaluation of the cognitive product: ideas are worth more the more widespread.
  • Exploitation (not waste) of the cognitive work force (David and Foray, 2001), thanks to the possibility of reusing the code and the existing text (be it musical, computer, scientific, didactic or any other type).

3.5 Technoscience as a policy

After highlighting the knowledge society as a risk society, the loaded nature of values of post-normal science practices, the insertion of the interests of the market economy in the process of techno-scientific production and pointing out the dominant power forces in research traditions, we have abandoned the criticism of techno-scientific production in denouncing the tendency of institutional policy to replace uncomfortable social policies in favor of R & D policies and in denouncing a process of progressive merchandising to know. Indeed up to this point the solution seems to be to abandon the linear model, to integrate the various social agents in a constructive and non-deterministic process of techno-scientific development, to open spaces for participation in the regulation of technoscience and to make membranes more permeable of the academic system.

The organization, financing and justification of techno-scientific products and practices, as well as the economic model based on innovation, are effectively reinforced by the complex of myths that we have exposed with Sarewitz, namely, the myth of a deterministic techno-scientific rationalization, autonomous, and necessarily benefactor.

But the process of techno-scientific rationalization can be interpreted as something more than a myth or an ideology imposed on society as a discourse that justifies the current state of techno-scientific organization from top to bottom. This critical task was undertaken by Marcuse and later by Habermas more than 30 years ago, and together with this new spaces of techno-scientific policy action are opened.

3.5.1 Technoscience as an ideology

As Marcuse and Habermas (1968) already pointed out, the trend of techno-scientific rationalization of the political sphere gradually replaces the spaces of communicative rationality, making technoscience to be discovered as (meta) ideology that seeks to substitute the irreplaceable: social construction processes aimed at defining the interests of society itself, a society that is progressively losing the ability to achieve socially binding communicative processes and is reduced to build its identity through the consumer products of the market in leisure time and a rational action ends – technoscientifically – articulated at work.

The peculiar performance of this ideology is that it dissociates the self-compression of the society from the reference system of the communicative action and of the concepts of the symbolically mediated interaction and replaces them by a scientific model. To the same extent, the culturally determined self-compression of a social world of life is replaced by the self-classification of men under the categories of rational action with respect to ends and adaptive behavior (Habermas, 1968, p.89).

But the ideology to which Habermas refers here is not an ideology in the sense of a narrative or discourse that legitimates as such a mode of domination, from top to bottom. It is rather a process of techno-scientific rationalization that as a constitutive process of the forces of production and social organization reveals itself as legitimation from the bottom up.

The paradox of a possible regulation or control of technoscience on the part of society is shown by the fact that the current form of technoscientific economy and rationality has been implanted in the constitutive processes of society itself. The greatest difficulty of the models of participatory and constructive regulation lies in the asymmetry that exists between the degree of autonomy of the techno-scientific economy and that of society. An asymmetry marked by the degree of control that the techno-scientific economy exercises over society: 

  1. modifying the context of selection of its innovation products (through advertising), 
  2. through cognitive labor exploitation
  3. dominating the regulation of public investment in science and technology
  4. commercializing cultural products and the collective cognitive heritage (while imposing control and restriction measures on the free circulation of knowledge and techniques -copyright, patents and restricted copying technologies).  

This dominance is accentuated when the indicators with which the public funding of technoscience is evaluated are reduced to the production of patents and published articles (generally under copyright), and, lately, consultancies are required from companies and DCRs (restricted circulation documents), studies of restricted use to companies) to obtain public funding for research projects.

3.5.2 Reduction of complexity: The nuclei of Power in Techno-Scientific Networks

The theory of the network of actors (Latour and Woolgar, 1986, Latour, 1999) shows how techno-scientific production hides processes of complexity reduction and power relations that hinder an open re-appropriation of techno-scientific products by society. According to this theory, the techno-cognitive communities are composed of human beings, apparatuses, institutions, electronic networks, publications and a long etcetera of mechanisms and agents in such a way that human beings can not be understood in isolation as producers of knowledge but only inserted in a complex network of references, artifacts and institutions. Even the techno-scientific product of these networks is reintroduced into the network itself, becoming one more actor. However, for the network to be productive, a reduction in complexity is required. In a process (that the authors denominate of translation) sub-networks of the process are represented by actantes that turn into black boxes (black-box) for the other components of the network. These actantes compress the complexity of the processes of the subnet that generates them to be able to be re-introduced with effectiveness in the processes of a wider network. In this way the black-box or actants become unified entities that are used by other actors in the network or become themselves actors. The point of translation thus becomes a space of power and control, in such a way that translational processes become a source of social order within the network itself, since they determine the assemblages of (re) organization of interactions within it. These black boxes not only hide the complexity produced, but the network of power relations and the discourses of the production subnet. 

Black boxes can take the form of tools (material artifacts), organizations (when represented by a human being) or key concepts (when they are the result of a cognitive process).

From this perspective it is understood that social participation in the process of techno-scientific production can not be reduced to regulation from the outside but must be introduced in the processes of production of the black boxes; that the polarization between the laboratory and society (with the aggravation of mediation by the market economy) is the greatest difficulty in building socially liberating technoscience. Two factors hinder the opening of that reduction of complexity that hide the network of power relations of the production sub-networks:

1. The growing complexity of techno-scientific production together with the hyper-specialization that is occurring in the process. Something that must be compensated by trans-disciplinary processes of communication and (re) elaboration of techno-scientific products.

2. The need for capitalist techno-economy to close the black boxes and hinder access to the processes they contain to increase competitiveness in innovation processes. A need that is satisfied through patents, company secrets, closed code in software development, opaque technologies, etc. A whole series of legal and technological mechanisms whose neutralization passes, once again, by demanding and disseminating copyleft licenses and transparent and openly modifiable technologies.

3.6 Recapitulation and Conclusions

The way in which the various levels of techno-scientific production are subject to:

1. Selective pressures, filters and transmission restrictions (copyright, patents, restrictive and opaque technologies, etc.),

2. Constraints of variability (restriction of possible theoretical and experimental variations) and

the reduction of complexity in the production of black boxes that condense the power relations of producing sub-networks

are determined by:

  • the high competitiveness and globalization of the capitalist economy that forces a permanent race for innovation, making the organization of techno-scientific production processes no longer respond to a supposed satisfaction of social needs but to survival in a global competitive market environment ,
  • the military industry, and
  • the power interests of various research traditions,
  • discover the political nature of the techno-scientific processes that are located at the root of:
  • the increase of production forces,
  • the organization of the society itself and
  • the legitimation of the political domain (divorced from the socially binding communicative processes)

in knowledge societies.

Conclusions

The objectivity of science (as intersubjectively contrastable rationality) should not be confused with an absolute image of reality, it is rather a process of production of conceptions of the world that is cut out on a scale of what is possible and that applied recursively on the reality (through technological practice) also ends up shaping our social world, our imaginary, our identity; a process whose consequences have a marked political character.

The solution is not to free technoscience from military and market interests to “restore” something like an original and pure moment of science (something impossible and that, on the other hand, would not guarantee the social re-appropriation of technoscientific production), but by inserting it in socially constitutive processes in a conscious way, by assuming the political burden of all techno-scientific process and building from it.

4 Situated autonomy: towards new forms of organization of techno-cognitive social power

We believe that part of the solution of the problems posed in the knowledge society come from the creation of autonomous research networks and locating them in the contexts of social self-organization, both social movements and parallel initiatives of open and collective techno-scientific construction (such as the free software movement6, initiatives of antagonistic telematics7, hack-labs8, tactical hacktivism9, etc.).

The structural difficulties of a regulation from outside the techno-scientific production, maintaining the polarity (mediated by the market) between laboratory and society, always subject to interests and the restriction of the diffusion of knowledge and techniques, demand, to the extent of the possible, the collective commitment to appropriate the technoscientific processes as a fundamental political space in our societies.

It is not so much about regulating or participating in a more or less constricted way in the processes of techno-scientific production, but about being a constituent part of the process, about being subjects of a socially situated technoscience, and not being subject to a technoscientific economy that is progressively becomes independent of social interests.

It is definitely about:

  • cutting that linearity that has marked the legitimization and organization of technoscientific processes
  • open broadcasting of information via broadcast channels
  • making transparent the black boxes of the techno-scientific production, to place ourselves in the digitalization interfaces that determine the forms of coding information in the digital universes
  • strengthening dynamics of collective creation
  • building spaces of trans-disciplinarity in which to construct critical and productive discourses that break with the barriers imposed by the scientific and technical super-specialization
  • building techno-scientific laboratories in the processes of social self-organization
  • and to make these laboratories objects of experimentation in collective intelligence, in new forms of organization of technoscientific production and diffusion.

It is a question, then, of re-appropriating critically and collectively the technoscientific processes, as constitutive and therefore political processes of the knowledge society; to merge communicatively binding spaces with those of techno-scientific production in autonomous and socially situated collective projects of research, learning and techno-scientific dissemination.

And it is, responding to this need that we have launched the Situated Autonomy project.

The term cybernetics comes from the Greek and refers to the helmsman of the ships of the time. Cybernetics is thus discovered as a techno-scientific practice aimed at discovering the nature of agency, of autonomy and subjectivity, of the complex network of systemic relations that define adaptation, control, communication and intelligence; both for control and for its opposite: freedom (both structured by communication processes).

The Principia Cybernetica12 project today collects an inexhaustible and participatory archive of classical cybernetics and some of its later developments.

4.2.2 Artificial life and biology

“These are the sciences made possible by technology, the technologies made possible by science. The world view we create is derived from the intimate interaction of technology and science with the eye of craft experience, shaped by the theoretical expectations within which we as scientists must live. (…) Wresting reliable knowledge from the world we study biology, as Koestler described it, an Act of Creation”13

(Rose, 1999, p.873)

Perhaps one of the disciplines inherited from cybernetics (not only in its content but also in its transdisciplinary character, experimental and open to the transgression of academic and technical borders) is Artificial Life (VA). Christened by Christopher Langton (1996) as “the study of life-as-it-could-be rather than life-as-we-know-it”14, the VA becomes a science of the possible, a study synthetic (constructive) bottom-up of the processes of self-organization, of biological and cultural evolution, of the origin of life, intelligence and communication in the natural and artificial universes. Through artificial simulation (computational, chemical, electronic, robotic …), the VA discovers the conditions of possibility, the constrictive possibilities of the organization of systems, overcoming the classical experimental statistical study by opening the possibility of (re) create artificial universes in which to experiment with new forms of interaction, communication networks, forms of intelligence and autonomy, spaces in which we permanently re-define the biological, neurological and social substrate that constitutes us.

But more than as a discipline some practitioners (Wheeler et al., 2002) consider (in an attempt to flee from academic institutionalization) the VA as a label under which to produce a series of techno-scientific tools applicable to areas as diverse as art, biology, philosophy, psychology, linguistics and robotics. And it is in this vocation of production of tools that we find in the VA a techno-cognitive space in which nature does not bend to mere operational domain space but becomes a companion to interrogate on the evolutionary and autonomous forms of symbiosis, collective intelligence, bacterial networks (Blissett, 2002), multicellularity or autopoiesis. Nature becomes co-investigator of the different ways of organizing our own identity, individual, collective, multiple.

4.2.3 Cognitive Sciences and Artificial Intelligence

“If one manages to simulate at the level of social systems the structure of rational action with respect to ends, man could not only, as homo faber, fully objectify himself for the first time and face his own automated products, but could also be integrated into its own technical apparatus such as homo fabricus.”

(Habermas, 1968, p.90)

Perhaps one of the most relevant techno-scientific spaces in the context of knowledge societies is that of cognitive sciences. If we allow research in cognitive sciences to become autonomous in the sphere of market innovation processes, we are playing our own creation. 

While the cognitive sciences objectify the human being as an object of study and insert it into the processes of techno-scientific production, the cognitive sciences become producers of scientific models of the human being (from intelligence tests to cognitive therapies) with the consequent transformation potential of understanding and structuring of ourselves and our forms of relationship and interaction in knowledge societies. From autonomous robotics to classical computationalist functionalism, through evolutionary psychology or connectionism, cognitive sciences, far from drawing a closed image of the human being, are in constant revolution and theoretical conflict. They discover a set of myths and beliefs that have chained the human being to certain forms of interaction (cognitive and social) derived from the theories or mythical conceptions that the human being constructs of himself; but also new forms of exploitation, reduction and aspiration of the human being are generated at the same time that criticisms, alternatives and unexplored possibilities arise. Reapproving these processes of techno-scientific production, critically dialoguing in and from them, adapting them and also knowing and / or not recognizing ourselves through them is a task as urgent as it is fascinating.

At the same time, cognitive sciences represent a kind of organizational science of the knowledge society, especially thanks to the development of artificial intelligence technologies and the cognitive organization sciences. This is the case of the creation of a semantic network inserted in the WWW (García Cataño and Arroyo Menéndez, 2002) in which the conceptual ontologies developed will determine the navigability form “intelligent” of the infospace or the artificial selection agents of information in the network. Equally important is the production of intelligent software that facilitates collective creation (Casacuberta, 2003), accessibility and participation in information repositories, etc.

Therefore, the cognitive sciences and artificial intelligence are in a privileged place of influence in the form acquired by the society of knowledge and the interaction of the human being; both by the effect of the objectification of the human being and by the artificial intelligence technologies that begin to configure the domains of cognitive interaction in cyberspace and in the set of interactive human spaces of a cognitive nature.

4.2.4 Towards a science of the possible

The Cognitive Sciences, the Cybernetics and the VA is thus shown as one of the strongest paradigms of science of the possible, one of the motivations exposed in Barandiaran (2003) and that we quote extensively here:

It is appropriate here to quote Ashby (pioneering cyberneticist of the 1950s) whose “An introduction to cybernetics”15 is an unbeatable and irreplaceable prelude to the sciences of the artificial: “Finally a set may be created by the fiat of the theoretician wh , not knowing which state a particular machine is at, wants to trace the consequences of all the possibilities. The set now is not the set of what does exist, but the set of what may exist (so far as the theoretician is concerned). This method is typically cybernetic, for it considers the current in relation to the wider set of the possible or the conceivable. “16 (Ashby, 1956, p.136) 

Indeed, cybernetics (and together with it the artificial life, contemporary heir of the foundations “forgotten” by classic cybernetics), overcomes the framework of what-exists-to think what can-exist (a dualism already present in the founding text of Life Artificial (Langton, 1996). We can make a rapid classification of sciences (classification that would require a more elaborate justification of the present here, but which nevertheless can serve as a powerful and stimulating intuition, always revisable) in three main groups:

  1. Sciences of the universal
  2. Sciences of the current
  3. Sciences of the possible

The first group includes physics, and in general the “strong” sciences (paradigm of traditional scientific epistemology). These sciences of the universal discover the laws of nature, whose applicability does not require specific constraints17, hence its marked objective, universal and necessary character. But science also delves into other spaces that are not so “universal”: life, the mind and the economy, to name a few. 

The current sciences work on what exists, seeks probabilistic predictions about some systems that surround us, extracts knowledge from a series of assumed conditions (DNA structure, rationality, stability of production processes, etc.) and the statistics obtained of the observed variables. The current sciences are incapable of “seeing” beyond what there is, sometimes condemning human knowledge to resigning itself to the present. 

Finally, the sciences of the possible work on the constraints that make possible the current, work on the conditions of possibility, on the variations of what makes the current possible from the universal. The science of the possible is asked by the “how” of the current discovering other possible realizables. This is the case of cybernetics and artificial life, systemic theory, complexity theory and non-Cartesian artificial intelligence. Thus, for example, the study of the conditions that make life possible: i.e. that make it possible for the dynamics of a system to close generating its own autonomy, discover “ life-as-could-be ” and, along with it, other possible ways of organizing the lives of those who surround

The science of the possible is revealed as well as technology, as a source of power, of being able to re-structure, recombine and reconstruct the modes of organization and production through the (simulated) experimentation of the constrictions or conditions of possibility of the same. The sciences of the possible (by overcoming a statistical study of what exists through the question of “what makes what exists”) open a space of action towards new modes of organization, towards new possible trajectories of a system: with a field of applicability that goes from biology to modes of human organization, through cognition and language.

(Barandiaran, 2003, §1.2)

In a techno-political space marked by biotechnology, social control with artificial intelligence techniques, legitimization of capitalism as self-regulated and self-organized and cognitive labor exploitation (among others), assume as research and learning contents cybernetics, artificial life and cognitive science is an urgent initiative. Even more so when this opening and critical re-appropriation of technoscientific processes also becomes a source of effective instruments and tools to coordinate horizontal communication, the self-organization of social processes, and collective communication and creation (Casacuberta, 2003); tools to increase, in short, our productive and organizational power outside the spaces of market power, war and academia.

Attentive always to the traps that the human being is permanently built to deceive himself, this project can not be disconnected from the critique of exploitation and capitalization of life and knowledge, instrumentalist conceptions of cognition and intelligence as well as of neo-spiritualist and pseudoscientific voices that flood the network (occupying the heartbreaking emptiness opened by the substitution of the communicative / symbolic spaces for the construction of the personal and collective identity by a rationality ends / means alienating and socialized through consumption).

4.3 Tactics

Universities have been transformed into overcrowded nurseries where taking notes and passing exams becomes the ritual of turn to access titles that determine competitive social status in knowledge societies. A meritocracy of titles that has replaced the passion to know, share and disseminate knowledge. Many students are aware of this situation and look for new, open and stimulating cognitive spaces. If we add to this that the number of students is far above the job opportunities linked to the chosen area of study and the number of young researchers who do not find techno-cognitive spaces that meet their objectives (in view of the commercialization and growing capitalization of research academic) we observe a growing waste of social cognitive forces (especially if it does not greas well its structure to fit into the domains of the market) and a frustration in the aspirations of those who wish to continue researching, learning and sharing knowledge.

That is why we believe that an autonomous and situated research project can in principle reach to mobilize the necessary cognitive force to be effective in its production, diffusion, and criticism. This has been the case of the process of setting up the free software community and, to a certain extent, of mediativist communities18. Socio-technical experiments parallel to ours whose success make us optimistic about the future possibilities of Situated Autonomy.

In the context of the techno-scientific development described in the previous sections, parasitizing the academic, institutional and labor commitments that are continually acquired in the knowledge society (whether in class work, research projects, etc.) is a legitimate and useful strategy for the construction of autonomous and situated techno-scientific spaces. 

Alumni researchers can integrate their academic work in collective intelligence projects (in which to participate actively, share resources, generate debate and produce technoscience), the labor technocognitive resources (unused outside working hours) can also be mobilized, the time of leisure can (and should) also be channeled out of the consumer and alienating leisure proposals. We have, in short, the necessary potential and the amount of economic resources necessary to carry out the initiative (in the techno-scientific content we have chosen in Situated Autonomy) whose investment needs are very small.

4.4 Development

In Situated Autonomy we already have a series of projects in operation and others in the process of development:

Virtual Assembly mailing list: The Gray-Walter19 mailing list serves as a communicative channel as a permanent assembly in which to discuss the internal lines of operation, the maintenance of the website, reading group, share various information and generate debates around projects and topics of interest.

Rhizomatic Repository: The Rhizomatic Repository is a free software application that allows to maintain a file of links with comments and assessment of the users. In this way we open our website to the contribution and participation of anyone who wishes to contribute to a wide archive of links to documents, web pages, bibliographies, etc.

Reading group: On the Gray-Walter mailing list we also carried out a reading group in which we discussed scheduled readings20. In the future the idea is to be able to invite investigators to participate in the discussion after reading some of their texts.

Creation and dissemination of documents: Generating own documents that contribute to the dissemination, translation, learning, criticism and research on the chosen topics is one of the fundamental objectives. For this we have chosen the copyleft license designed by Creative Commons attribution-noncomertial-sharealike21.

News and information: The central section of the website is intended to present news of techno-scientific interest and proposals, documents and initiatives of the group.

Technical Resources: A section of the web is dedicated to exposing the free software resources that we use to generate documents and programming, and to promote the networks of users * s / producers * s of them.

Research projects: Once we have advanced in the generation of basic documentation, resources and internal debate, we hope to be able to launch specific research projects.

4.5 Objectives

To finish we can collect the objectives (always revisable) of Autonomy Located in the following points:

Liberate techno-scientific spaces in the context of the copyleft community and the collective re-appropriation of techno-cognitive processes.

Generate autonomous techno-scientific power (articulated in horizontal processes of decision-making and independent of the interests of the market, war and academic power groups) and located in social and existential problems; i.e. assuming as their own and legitimate the interests derived from these problems.

Contribute to a technoscience of the possible that produces useful tools and critical discourse; in open, participatory and transparent processes (open source).

In short, we launched the open proposal to: Build an open, participatory and non-centralized network of research, learning, dissemination and techno-scientific criticism around cybernetics, artificial life and cognitive sciences; located and rooted in social and existential problems that constitute us as living, cognitive, communicative and social.

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Footnotes

… Gray-Walter1

grey-walter@sindominio.net

… impact. ” 2

Where previously the new technological projects had to be analyzed for their environmental impact, the progressively introduced regulations to mitigate this impact, now, contrarily, should be evaluated for their economic impact.

… mythology3

The five myths that Sarewitz reveals in his work are:

The myth of infinite benefit: that more science and more technology will lead to more public benefit. This is the myth on which the Bush linear model is based.

The myth of research equally beneficial: that any line of scientifically reasonable research on natural processes is as capable of generating social benefit as any other.

The myth of responsibility: that the “peer review”, the reproducibility of results and the control of the quality of scientific research reflect the main political responsibilities of the research system.

The myth of scientific authority: that scientific information provides an objective basis for the resolution of political problems.

The myth of the endless border: that the knowledge generated in the frontiers of science is independent of its moral and practical consequences in society.

Translated from (Sarewitz, 1996, pp.10-11)

… exchange.4

“ The relationship of suppliers and users of knowledge with the knowledge they provide and use is tending, and will progressively tend to acquire the form that has already taken the relationship between producers and consumers of goods with the goods they produce and consume – that is, the form of the value. Knowledge is produced and produced in order to be sold, consumed and consumed in order to acquire value in a new production: in both cases the objective is exchange. ”

… copyright5

We can here cite three of the most important referents of the copyleft community that have developed specific licenses:

The GNU project and the Free Software Foundation: http://www.gnu.org

Creative Commons: http://www.creativecommons.org

Art Libre – Copyleft Attitude: http://www.artlibre.org

… free6

http://gnu.org or http://debian.org

… antagonist7

http://indymedia.org

… hacklabs8

http://www.hacklabs.org

… tactical9

http://www.hactivist.com

… war.10

This section has been copied from http://sindominio.net/autonomiasituada/faq.html

… machine”11

The science of control and communication in the animal and the machine

… Cybernetica12

http://pespmc1.vub.ac.be

… Creation”13

“ These are the sciences made possible by technology, the technologies made possible by science. The vision of the world that we create is derived from the intimate interaction that is established between science and technology and the artisan experience, modeled by the theoretical expectations in which we live as biology theorists. (…) To extract reliable knowledge of the world that we biologists study is, as Koestler described it, an Act of Creation. ”

… life-as-we-know-it”14

The study of life-as-it-can-be instead of life-as-we-know-it.

… cybernetics”15

Released at: http://pespmc1.vub.ac.be/ASHBBOOK.html

… conceivable. “16

“Finally, a set can be created by the competence of the theoretician who, not knowing what state the machine is in, wants to discover the consequences of all the possibilities. The set, in this case, is not the whole of that which exists, but of that which can exist (insofar as it concerns the theorist). This method is typically cybernetic because it takes into account the current in relation to the broader set of what is possible or what is conceivable. ”

… constrictions17

The difference between law and constriction is of fundamental importance for this point: a law determines a space of prediction and universal and necessary applicability. The laws of physics are fulfilled regardless of the initial conditions of a system, they are general and absolute. Constraints (constraints), on the other hand, are the reduction of the variability of a system whose local dynamism is determined by laws: they include aspects such as initial conditions and boundary conditions. I explain, the emergence of life is not something derived exclusively from the laws of nature but of these plus a series of initial conditions and contour (temperature, molecular combinations based on carbon, autocatalytic processes, operational closure, etc.). that it is necessary to postulate and specify to explain or predict the origin of life. That is, a phenomenon such as life, to become a scientific object, is not simply specified by physical laws, but requires a series of information “extra”, not contained in universal laws. This extra information is that contained in the constrictions.

… mediaactivists18

http://indymedia.org

… Gray-Walter19

grey-walter@sindominio.net

… scheduled20

To date Varela (1992); Emmeche (1994); Dawkins (1986); Margulis and Sagan (1986).

… attribution-noncomertial-sharealike21

http://creativecommons.org/licenses/by-nc-sa/1.0/legalcode

… Copyleft22

copyleft@sindominio.net

Discovering Data Quality Rules

Discovering Data Quality Rules

Fei Chiang University of Toronto fchiang@cs.toronto.edu

Rene ́e J. Miller University of Toronto miller@cs.toronto.edu

Poor data quality continues to be a mainstream issue for many organizations. Having erroneous, duplicate or incomplete data leads to ineffective marketing, operational inefficiencies, inferior customer relationship management, and poor business decisions. It is estimated that dirty data costs US businesses over $600 billion a year [11]. There is an increased need for effective methods to improve data quality and to restore consistency.

Dirty data often arises due to changes in use and perception of the data, and violations of integrity constraints (or lack of such constraints). Integrity constraints, meant to preserve data consistency and accuracy, are defined according to domain specific business rules. These rules define relationships among a restricted set of attribute values that are expected to be true under a given context. For example, an organization may have rules such as: (1) all new cus- tomers will receive a 15% discount on their first purchase and preferred customers receive a 25% discount on all purchases; and (2) for US customer addresses, the street, city and state functionally determines the zipcode. Deriving a complete set of integrity constraints that accurately reflects an organization’s policies and domain semantics is a primary task towards improving data quality.

To address this task, many organizations employ consultants to develop a data quality management process. This process involves looking at the current data instance and identifying existing integrity constraints, dirty records, and developing new constraints. These new constraints are normally developed in consultation with users who have specific knowledge of business policies that must be enforced. This effort can take a considerable amount of time. Furthermore, there may exist domain specific rules in the data that users are not aware of, but that can be useful towards enforcing semantic data consistency. When such rules are not explicitly enforced, the data may become inconsistent.

Identifying inconsistent values is a fundamental step in the data cleaning process. Records may contain inconsistent values that are clearly erroneous or may potentially be dirty. Values that are clearly incorrect are normally easy to identify (e.g., a ’husband’ who is a ’female’). Data values that are potentially incorrect are not as easy to disambiguate (e.g., a ’child’ whose yearly ’salary’ is ’$100K’). The unlikely co-occurrence of these values causes them to become dirty candidates. Further semantic and domain knowledge may be required to determine the correct values.

For example,Table1showsasampleofrecordsfroma 1994 US Adult Census database [4] that contains records of citizens and their work class (CLS), education level (ED), marital status (MR), occupation (OCC), family relationship (REL), gender (GEN), and whether their salary (SAL) is

Dirty data is a serious problem for businesses leading to incorrect decision making, inefficient daily operations, and ultimately wasting both time and money. Dirty data often arises when domain constraints and business rules, meant to preserve data consistency and accuracy, are enforced incompletely or not at all in application code.

In this work, we propose a new data-driven tool that can be used within an organization’s data quality management process to suggest possible rules, and to identify conformant and non-conformant records. Data quality rules are known to be contextual, so we focus on the discovery of context-dependent rules. Specifically, we search for conditional functional dependencies (CFDs), that is, functional dependencies that hold only over a portion of the data. The output of our tool is a set of functional dependencies together with the context in which they hold (for example, a rule that states for CS graduate courses, the course number and term functionally determines the room and instructor). Since the input to our tool will likely be a dirty database, we also search for CFDs that almost hold. We return these rules together with the non-conformant records (as these are potentially dirty records).

We present effective algorithms for discovering CFDs and dirty values in a data instance. Our discovery algorithm searches for minimal CFDs among the data values and prunes redundant candidates. No universal objective measures of data quality or data quality rules are known. Hence, to avoid returning an unnecessarily large number of CFDs and only those that are most interesting, we evaluate a set of interest metrics and present comparative results using real datasets. We also present an experimental study showing the scalability of our techniques.

Lens Source

Establishing Governance Rules Over Data Assets

LENS source.


(54) ESTABLISHING GOVERNANCE RULES OVER DATA ASSETS
(75) Inventor: International Business Machines Corporation,  Armonk, NY (US)
(73) Assignee: International Business Machines Corporation,  Armonk, NY (US), Type: US Company
(*) Notice: Subject to any disclaimer, the term of this patent is extended or adjusted under 35 U.S.C. 154(b) by 0 days.
(21) Appl. No.: 15/014,329
(22) Filed: Feb.  3, 2016
Related U.S. Patent Documents
(63) . Continuation of application No. 14/929,510, filed on Nov.  2, 2015 .

Jan.  1, 2013 G 06 F 17 30604 F I Jan.  31, 2017 US B H C Jan.  1, 2013 G 06 F 17 30598 L I Jan.  31, 2017 US B H C

(51) Int. Cl. G06F 007/00 (20060101); G06F 017/00 (20060101); G06F 017/30 (20060101)
(58) Field of Search 707/694

 

(56) References Cited
U.S. PATENT DOCUMENTS
8,700,577   B2 4/2014     Yeh et al.
2009//0063534   A1 3/2009     Halberstadt
2010//0114628   A1 5/2010     Adler et al.
2011//0066602   A1 3/2011     Studer et al.
2012//0102007   A1 4/2012     Ramasubramanian et al.
2013//0031044   A1 * 1/2013     Miranda 706/47

 

FOREIGN PATENT DOCUMENTS
WO 2007038231 A2 4/2007

 

OTHER PUBLICATIONS
Chiang et al., “Discovering Data Quality Rules”, VLDB ’08, Aug. 24-30, 2008, Auckland, New Zealand, Copyright 2008 VLDB Endowment, ACM, 12 pages.
Appendix P.: List of Patents or Patent Applications Treated as Related, 2 pages.
U.S. Appl. No. 14/929,510, Entitled “Establishing Governance Rules Over Data Assets”, filed Nov. 2, 2015, IBM.
List of IBM Patents or Patent Applications Treated as Related, Appendix P, Filed Herewith, 2 pages.
Halberstadt, et al., “Establishing Governance Rules Over Data Assets”, U.S. Appl. No. 15/014,329, filed Feb. 3, 2016.
     * cited by examiner
     Primary Examiner —Van Oberly
     Art Unit — 2166
     Exemplary claim number — 1
(74) Attorney, Agent, or Firm — Lance I. Hochhauser

 

(57)

Abstract

Transform governance rules for a data asset to apply to a set of related data assets. Establishing a governance rule over a first data asset based on a second governance rule applied to either an upstream or a downstream data asset.
1 Claim, 3 Drawing Sheets, and 5 Figures

BACKGROUND

[0001] The present invention relates generally to the field of data processing, and more particularly to data integrity.
[0002] Data assets are used to run operational systems of businesses. Businesses employ governance rules to ensure that data assets comply with external and/or internal regulations. For example, in banking, external regulations come from voluntary agreements (the Third Basel Accord, or Basel III) or government agencies (FDIC regulations), and internal regulations come from a variety of standards and practices put in place by a management group of a business such as exceeding external regulations or supplementing external regulations (e.g., personnel, physical security). To comply with both internal and external regulations, businesses employ a variety of governance rules (sometimes also called data rules).
[0003] Applying governance rules to data assets can be manually intensive. Application of governance rules can also include a variety of errors. To apply a governance rule, all data assets under the governance rule must be located, data within the data assets must be understood, and the governance rule must be applied correctly to the data assets. Generally, these abilities are not centrally located and various knowledge bases must be combined.

SUMMARY

[0004] According to an aspect of the present invention, there is a method, computer program product, and/or system that performs the following operations (not necessarily in the following order): (i) determining a relationship between a first data asset and a second data asset; (ii) determining a first governance rule applied to the first data asset; and (iii) transforming the first governance rule, into a second governance rule, based on the relationship between the first data asset and the second data asset. At least determining a relationship between a first data asset and a second data asset is performed by computer software running on computer hardware.

BRIEF DESCRIPTION OF THE DRAWINGS

[0005] FIG. 1 is a block diagram view of a first embodiment of a system according to the present invention;
[0006] FIG. 2 is a flowchart showing a first embodiment method performed, at least in part, by the first embodiment system;
[0007] FIG. 3 is a block diagram view of a machine logic (e.g., software) portion of the first embodiment system;
[0008] FIG. 4 is a screenshot showing a data lineage graph according to a second embodiment of a system according to the present invention; and
[0009] FIG. 5 is a screenshot showing a pseudocode according to a third embodiment of a system according to the present invention.

DETAILED DESCRIPTION

[0010] Transform governance rules for a data asset to apply to a set of related data assets. Establishing a governance rule over a first data asset based on a second governance rule applied to either an upstream or a downstream data asset. This Detailed Description section is divided into the following sub-sections: (i) Hardware and Software Environment; (ii) Example Embodiment; (iii) Further Comments and/or Embodiments; and (iv) Definitions.

I. HARDWARE AND SOFTWARE ENVIRONMENT

[0011] The present invention may be a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention.
[0012] The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.
[0013] Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device.
[0014] Computer readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++, or the like, and procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user’s computer, partly on the user’s computer, as a stand-alone software package, partly on the user’s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user’s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention.
[0015] Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.
[0016] These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks.
[0017] The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
[0018] The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.
[0019] An embodiment of a possible hardware and software environment for software and/or methods according to the present invention will now be described in detail with reference to the Figures. FIG. 1 is a functional block diagram illustrating various portions of networked computers system 100, including: governance relationship sub-system 102; data asset sub-systems 104, 106; rule storage sub-system 108; and communication network 114. Governance relationship sub-system 102 contains: governance relationship computer 200; display device 212; and external devices 214. Governance relationship computer 200 contains: communication unit 202; processor set 204; input/output (I/O) interface set 206; memory device 208; and persistent storage device 210. Memory device 208 contains: random access memory (RAM) devices 216; and cache memory device 218. Persistent storage device 210 contains: governance relationship program 300. Data asset sub-system 104 contains: first data asset 220; second data asset 222; data asset storage 224; and governance rule storage 226.
[0020] Governance relationship sub-system 102 is, in many respects, representative of the various computer sub-systems in the present invention. Accordingly, several portions of governancerelationship sub-system 102 will now be discussed in the following paragraphs.
[0021] Governance relationship sub-system 102 may be a laptop computer, a tablet computer, a netbook computer, a personal computer (PC), a desktop computer, a personal digital assistant (PDA), a smart phone, or any programmable electronic device capable of communicating with client sub-systems via communication network 114. Governance relationship program 300 is a collection of machine readable instructions and/or data that is used to create, manage, and control certain software functions that will be discussed in detail, below, in the Example Embodiment sub-section of this Detailed Description section.
[0022] Governance relationship sub-system 102 is capable of communicating with other computer sub-systems via communication network 114. Communication network 114 can be, for example, a local area network (LAN), a wide area network (WAN) such as the Internet, or a combination of the two, and can include wired, wireless, or fiber optic connections. In general, communication network 114 can be any combination of connections and protocols that will support communications between governance relationship sub-system 102 and client sub-systems.
[0023] Governance relationship sub-system 102 is shown as a block diagram with many double arrows. These double arrows (no separate reference numerals) represent a communications fabric, which provides communications between various components of governance relationship sub-system 102. This communications fabric can be implemented with any architecture designed for passing data and/or control information between processors (such as microprocessors, communications processors, and/or network processors, etc.), system memory, peripheral devices, and any other hardware components within a system. For example, the communications fabric can be implemented, at least in part, with one or more buses.
[0024] Memory device 208 and persistent storage device 210 are computer readable storage media. In general, memory device 208 can include any suitable volatile or non-volatile computer readable storage media. It is further noted that, now and/or in the near future: (i) external devices 214 may be able to supply some, or all, memory for governance relationship sub-system 102; and/or (ii) devices external to governance relationship sub-system 102 may be able to provide memory for governance relationship sub-system 102.
[0025] Governance relationship program 300 is stored in persistent storage device 210 for access and/or execution by one or more processors of processor set 204, usually through memory device 208. Persistent storage device 210: (i) is at least more persistent than a signal in transit; (ii) stores the program (including its soft logic and/or data) on a tangible medium (such as magnetic or optical domains); and (iii) is substantially less persistent than permanent storage. Alternatively, data storage may be more persistent and/or permanent than the type of storage provided by persistent storage device 210.
[0026] Governance relationship program 300 may include both substantive data (that is, the type of data stored in a database) and/or machine readable and performable instructions. In this particular embodiment (i.e., FIG. 1), persistent storage device 210 includes a magnetic hard disk drive. To name some possible variations, persistent storage device 210 may include a solid-state hard drive, a semiconductor storage device, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, or any other computer readable storage media that is capable of storing program instructions or digital information.
[0027] The media used by persistent storage device 210 may also be removable. For example, a removable hard drive may be used for persistent storage device 210. Other examples include optical and magnetic disks, thumb drives, and smart cards that are inserted into a drive for transfer onto another computer readable storage medium that is also part of persistent storage device 210.
[0028] Communication unit 202, in these examples, provides for communications with other data processing systems or devices external to governance relationship sub-system 102. In these examples, communication unit 202 includes one or more network interface cards. Communication unit 202 may provide communications through the use of either or both physical and wireless communications links. Any software modules discussed herein may be downloaded to a persistent storage device (such as persistent storage device 210) through a communications unit (such as communication unit 202).
[0029] I/O interface set 206 allows for input and output of data with other devices that may be connected locally in data communication with governance relationship computer 200. For example, I/O interface set 206 provides a connection to external devices 214. External devices 214will typically include devices, such as a keyboard, a keypad, a touch screen, and/or some other suitable input device. External devices 214 can also include portable computer readable storage media, such as, for example, thumb drives, portable optical or magnetic disks, and memory cards. Software and data used to practice embodiments of the present invention (e.g., governancerelationship program 300) can be stored on such portable computer readable storage media. In these embodiments, the relevant software may (or may not) be loaded, in whole or in part, onto persistent storage device 210 via I/O interface set 206. I/O interface set 206 also connects in data communication with display device 212.
[0030] Display device 212 provides a mechanism to display data to a user and may be, for example, a computer monitor or a smart phone display screen.
[0031] The programs described herein are identified based upon the application for which they are implemented in a specific embodiment of the invention. However, it should be appreciated that any particular program nomenclature herein is used merely for convenience, and thus the invention should not be limited to use solely in any specific application identified and/or implied by such nomenclature.
[0032] The descriptions of the various embodiments of the present invention have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

II. EXAMPLE EMBODIMENT

[0033] FIG. 2 shows flowchart 250 depicting a method according to the present invention. FIG. 3shows governance relationship program 300, which performs at least some of the method operations of flowchart 250. This method and associated software will now be discussed, over the course of the following paragraphs, with extensive reference to FIG. 2 (for the method operation blocks) and FIG. 3 (for the software blocks). In this example, John is performing a scientific experiment wherein a thermometer records water temperatures in degrees Fahrenheit, but a later step requires water temperatures in degrees Celsius.
[0034] Processing begins at operation 5255, where determine first data asset module (“mod”) 302determines a first data asset. A data asset is sometimes also called a node or a data set. A first data asset is sometimes also called a current node. A data asset can be a set of related data that is manipulated to determine a result. The use of “first” to describe a first data asset does not indicate a relative position of the first data asset in a grouping of data assets; “first” is used merely to distinguish a first data asset from other data assets. For example, a “first” data asset can be an upstream data asset as compared to a “second” data asset; however, a “first” data asset can also be a downstream data asset as compared to a “second” data asset. In some embodiments of the present invention, determine first data asset mod 302 determines a first data asset is stored in data asset storage 224. In this example, determine first data asset mod 302 determines first data asset 220 is a record of water temperatures, recorded in degrees Fahrenheit.
[0035] Processing proceeds to operation S260, where determine rule mod 304 determines a governance rule for a first data asset. A governance rule is a restriction of a data asset. A governance rule is sometimes also called a data quality rule or a first governance rule. In some embodiments of the present invention, a governance rule is a range to which data in a data asset must conform. Alternatively, a governance rule indicates a different restriction on a data asset including, but not limited to: (i) determining a datum is not null; (ii) determining a datum conforms to a format; (iii) determining a datum is selected from a defined group; (iv) determining a datum is within a range of values; (v) determining a datum contains allowed characters; and/or (vi) determining a datum conforms to a format requiring special treatment (e.g., a social security number, a credit card number). In some embodiments of the present invention, determine rule mod 304 determines a governance rule from metadata associated with a first data asset. Alternatively, determine rule mod 304 determines a governance rule based, at least in part, on a stored governance rule. In some embodiments of the present invention, a governance rule is stored in a location local to a first data asset. Alternatively, a governance rule is stored in a location remote from a first data asset; for example, a first data asset is stored on data asset sub-system 106, and a governance rule is stored on rule storage sub-system 108. In this example, determine rule mod 304 determines that a data governance rule is stored in governance rule storage 226. Determine rule mod 304 determines that the governance rule restricts data in the first data asset to values between 32 and 212 (i.e., 32 degrees Fahrenheit and 212 degrees Fahrenheit). This is because the thermometer is measuring the temperature of water.
[0036] Processing proceeds to operation S265, where determine second data asset mod 306determines a second data asset. The use of “second” to describe a second data asset does not indicate a relative position of the second data asset in a grouping of data assets; “second” is used merely to distinguish a second data asset from other data assets. A second data asset is sometimes also called a next node. In some embodiments of the present invention, determine second data asset mod 306 determines a second data asset is stored in data asset storage 224. In this example, determine second data asset mod 306 determines second data asset 222 is a record of water temperatures, recorded in degrees Celsius.
[0037] Processing proceeds to operation S270, where determine relationship mod 308 determines a relationship between a first data asset and a second data asset. A relationship between two data assets is sometimes also called an edge. In some embodiments of the present invention, a relationship between a first data asset and a second data asset is one of: (i) a direct-write relationship (i.e., the second data asset writes to the first data asset); (ii) an indirect-write relationship (i.e., the second data asset propagates write commands, through one or more intervening data assets, to the first data asset); (iii) a direct-read relationship (i.e., the second data asset reads from the first data asset); or (iv) an indirect-read relationship (i.e., the second data asset propagates read commands, through one or more intervening data assets, to the first data asset). In this example, determine relationship mod 308 determines that second data asset 222 has a direct-read relationship with first data asset 220.
[0038] Processing proceeds to operation S275, where transform mod 310 transforms a governancerule. Transform mod 310 transforms a governance rule into a transformed governance rule (sometimes also called a second governance rule) based, at least in part, on a relationship between a first data asset and a second data asset. In some embodiments of the present invention, transform mod 310 determines how a relationship between a first data asset and a second data asset transforms a governance rule to a transformed governance rule. In some embodiments of the present invention, transform mod 310 determines how an indirect relationship transforms a governance rule to a transformed governance rule. In some embodiments of the present invention, transform mod 310 performs an extract, transform, load process. In some embodiments of the present invention, an extract, transform, load process includes extracting a governance rule, transforming the governance rule into a transformed governance rule, and loading the transformed governance rule. In some embodiments of the present invention, transform mod 310extracts a governance rule from a governance rule storage. In some embodiments of the present invention, transform mod 310 extracts a governance rule from a relationship between a first data asset and a second data asset. In some embodiments of the present invention, transform mod 310extracts a governance rule from a first data asset. In some embodiments of the present invention, transform mod 310 loads a governance rule to a governance rule storage. In some embodiments of the present invention, transform mod 310 loads a governance rule to a relationship between a first data asset and a second data asset. In some embodiments of the present invention, transform mod 310 loads a governance rule to a second data asset. In some embodiments of the present invention, transform mod 310 saves a transformed governance rule to governance rule storage 226.
[0039] In this example, transform mod 310 determines that data in first data asset 220 is converted to data in second data asset 222 by: first, subtracting 32; and, second, dividing by 1.8. Therefore, transform mod 310 transforms the governance rule, restricting first data asset 220 to a range of 32 to 212, into transformed governance rule, restricting second data asset 222 to a range of 0 to 100 (i.e., 0 degrees Celsius to 100 degrees Celsius). Alternatively, if a first data asset is in degrees Celsius and a second data asset is in degrees Fahrenheit, transform mod 310 transforms a governance rule by: first, multiplying by 1.8; and, second, adding 32.
[0040] In an alternative example, a first data asset is a downstream data asset and a second data asset is an upstream data asset. The second data asset has an indirect-write relationship with the first data asset. Each of the first data asset and second data asset represent dates. The first data asset is a number representing a number of days after a known date; the second data asset is a date in a written format (e.g., Jan. 1, 2016). Data in the second data asset is received as an input and is converted to data in an intermediate data asset, numerical representations of written dates. Data in the intermediate data asset is converted to data in the first data asset. The governance rule restricts the first data asset to dates after the known date. Therefore, transform mod 310transforms the governance rule into the transformed governance rule by transforming the number representing the known date (e.g., 0) into a numerical representation of the date (e.g., 5845), then transforming the numerical representation of the date into a written date (e.g., Jan. 1, 2016). Therefore, the transformed governance rule restricts the second data asset to dates after Jan. 1, 2016.
[0041] Processing terminates at operation 5280, where apply mod 312 applies a transformed governance rule to a second data asset. In some embodiments of the present invention, apply mod 312 restricts data in a second data asset based, at least in part, on a transformed governancerule. In some embodiments of the present invention, restricting data based, at least in part, on a transformed governance rule includes deleting and/or eliminating data in a second data asset that violates the transformed governance rule. In some embodiments of the present invention, restricting data based, at least in part, on a transformed governance rule includes not permitting new data that violates the transformed governance rule.

III. FURTHER COMMENTS AND/OR EMBODIMENTS

[0042] Some embodiments of the present invention recognize the following facts, potential problems, and/or potential areas for improvement with respect to the current state of the art: (i) data stewards maintaining data assets are prone to mistakes; (ii) maintenance of data assets (sometimes also called data records) is time intensive; and/or (iii) maintenance of data assets is resource intensive.
[0043] FIG. 4 depicts a screenshot of data lineage graph 400. Data lineage graph 400 contains: production run 405; staging 415; and product 425. Data lineage graph 400 depicts a flow of a datum from a first data asset to a second data asset. The first data asset in data lineage graph 400is production run 405. Production run 405 is a table containing various data, including a plant identifications (IDs) 410, a column in the table. The second data asset in data lineage graph 400 is product 425. Product 425 is also a table containing various data, including plant 430, a column in the table. Staging 415 is an export web service that reads data from plant IDs 410 and writes data to plant 430. Staging 415 also contains lookup table 420. Lookup table 420 is a table that contains an association between various plant IDs and associated plant names. In this example, plant IDs 410 contains a numerical representation of various plants (e.g., 1, 2, etc.). Staging 415 reads the numerical representation in plant IDs 410, converts the plant ID to a plant name, and writes the plant name to plant 430. In this example, plant 430 contains a data quality rule (sometimes also called a data governance rule) that plant names must be one of: Oregon, Texas, or California. In lookup table 420: the plant ID for Oregon is 1; the plant ID for Texas is 2; and the plant ID for California is 3. Therefore, staging 415 applies the data quality rule to production run 405 and determines data read from plant IDs 410 must be one of 1, 2, or 3.
[0044] In some embodiments of the present invention, a governance relationship sub-system employs recursive tracing of nodes and/or edges to determine relationships among various nodes. In some embodiments of the present invention, a governance relationship sub-system employs computer code based, at least in part, on a pseudo code. One example of pseudo code used by a governance relationship sub-system is shown in Table 1.
[0045] FIG. 5 depicts screenshot 500 showing pseudocode 510. Pseudocode 510 is pseudocode for traversing edges. In this example, “CurrentNode” is a first data asset, “NextNode” is a related second data asset, and “Edge” is a relationship between “CurrentNode” and “NextNode.” In some embodiments of the present invention, “Edge” is an ETL process. “TraverseEdges” is a recursive process that cascades (sometimes also called propagates) a governance rule from a first data asset to a second data asset, then determines if the rule should be cascaded to a third data asset. “TraverseEdges” takes a data asset as an argument. First, “TraverseEdges” check if the governancerule has already been applied to “CurrentNode” using “HasVisited.” “HasVisited” is a process that determines if a data asset has already been processed and takes “CurrentNode” as an argument. If “CurrentNode” has been processed, “TraverseEdges” is completed and processing returns to the process that called “TraverseEdges.” “TraverseEdges” then determines that “CurrentNode” has a set of “Edges” and a set of “NextNodes.” If “CurrentNode” does not have a set of edges or if “CurrentNode” does not have a set of “NextNodes,” “TraverseEdges” is completed and processing returns to the process that called “TraverseEdges.” “TraverseEdges” then checks if “CurrentNode” has a governance rule using “HasRule.” “HasRule” is a process that determines if a data asset has a governance rule. If “CurrentNode” does have a governance rule, “TraverseEdges” calls “ApplyRule.” “ApplyRule” is a process that applies a governance rule from a first data asset to a second data asset. In some embodiments of the present invention, “ApplyRule” is an ETL process. “ApplyRule” takes three arguments: (i) “CurrentNode”; (ii) “Edge”; and (iii) “NextNode.” “ApplyRule” takes the governance rule from “CurrentNode,” transforms the governance rule using “Edge,” then applies transformed governance rule to “NextNode.” “TraverseEdges” then calls itself to cascade governance rules through the set of related data assets.
[0046] In some embodiments of the present invention, traversing an edge is a recursive manner of checking a set of nodes to determine relationships among the nodes. In some embodiments of the present invention, a governance relationship sub-system ensures nodes are not processed multiple times. In some embodiments of the present invention, a governances relationship sub-system applies a rule from a current node to a next node. In some embodiments of the present invention, a governance relationship sub-system applies a rule recursively over a lineage graph. In some embodiments of the present invention, a governance relationship sub-system displays a set of nodes as a lineage graph.
[0047] In some embodiments of the present invention, a data asset has a quality governance rule regarding format of data. In this example, a governance rule requires that ninety percent (90%) of data values in a data asset must be of the pattern “x@y,” wherein each of “x” and “y” are non-null strings. A function of this type is sometimes called a concatenation function. In some embodiments of the present invention, a governance rule is applied to a concatenation function containing more than two arguments. To achieve the ninety percent quality required, a governance relationship sub-system applies the governance rule to the data assets “x” and “y.” Various possible combinations exist for applying governance rules to “x” and “y,” including, but not limited to: (i) one hundred percent (100%) of data values in data asset “x” must be non-null strings and ninety percent (90%) of data values in data asset “y” must be non-null strings; (ii) ninety percent (90%) of data values in data asset “x” must be non-null strings and one hundred percent (100%) of data values in data asset “y” must be non-null strings; and (iii) ninety-five percent (95%) of data values in data asset “x” must be non-null strings and ninety-five percent (95%) of data values in data asset “y” must be non-null strings. In some embodiments of the present invention, a governance relationship sub-system applies governance rules related to various concatenation functions to various data assets.
[0048] In some embodiments of the present invention, a governance rule relates to unit conversion. In this example, a governance rule requires temperatures in the range of 0 degrees Celsius to 100 degrees Celsius. To achieve the required data quality, a governance relationship sub-system applies an ETL process containing a conversion function, converting values from degrees Fahrenheit to degrees Celsius. The governance relationship sub-system applies the governance rule to the upstream data asset (the temperatures in degrees Fahrenheit), requiring that each value be in the range of 32 degrees Fahrenheit to 212 degrees Fahrenheit. In some embodiments of the present invention, a governance relationship sub-system applies governancerules related to various conversion functions to various data assets.
[0049] In some embodiments of the present invention, a governance rule relates to a lookup function. In this example, a governance rule requires a two letter country code selected from a group consisting of: DE, FR, UK, and US. For example, these countries are locations of manufacturing plants for a company. To achieve the required data quality, a governancerelationship sub-system applies an ETL process containing a lookup function, to determine a corresponding numerical representation for each of the two letter country codes (e.g., DE is 1, FR is 2, UK is 3, and US is 4). The governance relationship sub-system applies the governance rule to the corresponding data asset, in which the numerical representations for each country are used, requiring that each value be selected from a group consisting of: 1, 2, 3, and 4. In some embodiments of the present invention, a governance relationship sub-system applies governancerules related to various lookup functions to various data assets.
[0050] In some embodiments of the present invention, a governance rule relates to a pivot function. In some embodiments of the present invention, a governance relationship sub-system uses a pivot function in combination with a conversion function and/or a lookup function. In this example, a company has employees in various countries around the world. On a data asset containing a list of all employees, the country of each employee, and the salary of each employee, a governance rule requires a salary to be of the format “$dddd.dd.” Based, at least in part, on the country of the employee, a governance relationship sub-system applies an ETL function to pivot the salary column from various currencies to U.S. dollars. Additionally, based at least in part, on the country of the employee, a governance relationship sub-system applies an ETL function to pivot the governance rule format of “$dddd.dd” to various other currencies (e.g., [see pdf for image] eeee.ee, £pppp.pp, etc.). In some embodiments of the present invention, a governancerelationship sub-system takes a first data asset and converts it to a second data asset. For example, the first data asset is a table with the columns: name, salary, and country. A governancerelationship sub-system converts this first data asset to a second data asset with the columns: name, salary in Germany, salary in France, salary in the United Kingdom, and salary in the United States.
[0051] In some embodiments of the present invention, a governance rule relates to a merge and join function. In some embodiments of the present invention, a governance relationship sub-system uses a merge and join function in combination with a concatenation function. In some embodiments of the present invention, a governance relationship sub-system uses a merge and join function to combine two data assets into a single data asset. For example, a first data asset is a table with the columns: name, age, email, and address; a second data asset is a table with the columns: name, credit rating, and orders. A governance relationship sub-system would apply a merge and join function to create a single data asset with the columns: name, age, email, address, credit rating, and orders. Additionally, if any of the names in the first data asset and the names in the second data asset match up those entries are combined.
[0052] In some embodiments of the present invention, a governance rule employs a combination of one or more of the above functions to apply a governance rule to a data asset.
[0053] Some embodiments of the present invention may include one, or more, of the following features, characteristics, and/or advantages: (i) reducing time required to establish data assets; (ii) reducing resources required to establish data assets; (iii) reducing time required to maintain data assets; (iv) reducing resources required to maintain data assets; and/or (v) reducing a likelihood of errors in maintaining data assets.
[0054] In some embodiments of the present invention, a data asset exists within a larger data flow. In some embodiments of the present invention, an upstream process describes an upstream data asset writing information to a downstream data asset. In some embodiments of the present invention, a downstream process describes an downstream data asset reading information from an upstream data asset.
[0055] Some embodiments of the present invention may include one, or more, of the following features, characteristics, and/or advantages: (i) an “extract, transform, load” (ETL) job; (ii) an ETL job reading from an operational system; (iii) an ETL job writing to a data warehouse; (iv) a data lifecycle management tool; (v) a data lifecycle management tool reading from a warehouse; and/or (vi) a data lifecycle management tool creating a set of test data.
[0056] Some embodiments of the present invention may include one, or more, of the following features, characteristics, and/or advantages: (i) a reporting cube; (ii) a reporting cube reading from a data mart; (iii) a reporting cube enabling data analytics; (iv) a data lineage graph; (v) a data lineage graph depicting a set of upstream processes; (vi) a data lineage graph depicting a set of upstream data assets; (vii) a data lineage graph depicting a set of downstream processes; (viii) a data lineage graph depicting a set of downstream data asset; (ix) a data lineage graph depicting upstream processes that write to a data asset; and/or (x) a data lineage graph depicting downstream processes that read from a data asset.
[0057] Some embodiments of the present invention may include one, or more, of the following features, characteristics, and/or advantages: (i) locating a data asset within a data lineage graph; (ii) locating a data asset with a governance rule; (iii) applying a governance rule to a downstream data asset; (iv) applying a governance rule to an upstream data asset; (v) examining a relationship between two data assets; (vi) transforming a governance rule; (vii) transforming a governance rule based, at least in part, on a relationship between two data assets; (viii) adjusting a governance rule based, at least in part, on a manipulation of a first data asset into a second data asset; and/or (ix) recursively applying governance rules to related data assets. In some embodiments of the present invention, recursive application of a governance rule involves applying a governance rule to a set of data assets, wherein each sequential data asset exists in a direct-read relationship with the prior data asset. In some embodiments of the present invention, recursive application of a governancerule involves applying a governance rule to a set of data assets, wherein each sequential data asset exists in a direct-write relationship with the prior data asset.
[0058] Some embodiments of the present invention may include one, or more, of the following features, characteristics, and/or advantages: (i) analyzing a data lineage; (ii) applying a governancerule to a data asset; (iii) moving data among a set of data assets; (iv) transforming data among a set of data assets; (v) scaling an ETL platform; (vi) applying a governance rule to a data asset; (vii) using a set of stages to create jobs; (viii) moving data from a source data asset to a target data asset; (ix) capturing a set of jobs involved in moving data; (x) capturing a set of data assets involved in moving data; and/or (xi) displaying jobs in a data lineage graph.
[0059] Some embodiments of the present invention may include one, or more, of the following features, characteristics, and/or advantages: (i) using a data lineage graph to find an upstream job from a data asset; (ii) using a data lineage graph to find a downstream job from a data asset; (iii) analyzing a set of stages of a job (sometimes also called a process); (iv) analyzing a set of stages of a job to understand a nature of the job; (v) analyzing a governance rule to understand a meaning of the governance rule; and/or (vi) deducing a governance rule for a related data asset in a data lineage graph.
[0060] Some embodiments of the present invention may include one, or more, of the following features, characteristics, and/or advantages: (i) defining a key attribute of a governance rule; (ii) determining a set of data assets having governance rules; (iii) invoking a lineage to create a data lineage graph; (iii) applying a pseudo code; and/or (iv) applying a pseudo code to process a data lineage graph. In some embodiments of the present invention, a key attribute of a governance rule is a quality rule. Alternatively, a key attribute of a governance rule includes, but is not limited to: (i) a security rule; and/or (ii) a lifecycle rule.
[0061] Some embodiments of the present invention may include one, or more, of the following features, characteristics, and/or advantages: (i) a data lineage graph consisting of a set of nodes (sometimes also called data assets); (ii) a data lineage graph consisting of a set of edges (sometimes also called relationships among data assets); (iii) a governance relationship sub-system tracing a data lineage graph; (iv) a governance relationship sub-system determining an upstream data asset to be governed; (v) a governance relationship sub-system determining a downstream data asset to be governed; (vi) a governance relationship sub-system determining a governance rule to be applied to fulfil a set of governance requirements; (vii) a governancerelationship sub-system invoking a data lineage; and/or (viii) a governance relationship sub-system producing a data lineage graph.
[0062] Some embodiments of the present invention may include one, or more, of the following features, characteristics, and/or advantages: (i) finding a data lineage graph for a data asset; (ii) applying a governance rule to a data asset; (iii) applying a governance rule from a second data asset to a first data asset; (iv) applying a governance rule from a second data asset to a first data asset, based, at least in part, on a data lineage graph; (v) adapting a governance rule based, at least in part, on a transformation in a data lineage graph; and/or (vi) adapting a governance rule based, at least in part, on a transformation from a first data asset to a second data asset.
[0063] Some embodiments of the present invention may include one, or more, of the following features, characteristics, and/or advantages: (i) assigning governance rules to data assets in a regulatory report; (ii) invoking a data lineage for a data asset in a regulatory report; (iii) finding an ETL process for a data asset in a regulatory report; (iv) finding an upstream data asset in a regulatory report; (v) finding a downstream data asset in a regulatory report; (vi) analyzing an upstream ETL process in a regulatory report; (vii) analyzing a downstream ETL process in a regulatory report; (viii) adjusting a governance rule of a regulatory report; (ix) assigning an adjusted governance rule to an upstream asset; and/or (x) assigning an adjusted governance rule to an downstream asset.
[0064] Some embodiments of the present invention may include one, or more, of the following features, characteristics, and/or advantages: (i) adhering to financial regulations; (ii) adhering to banking regulations (e.g., Basel III); and/or (iii) reducing effort to adhere to regulations.
[0065] Some embodiments of the present invention may include one, or more, of the following features, characteristics, and/or advantages: (i) using data lineage to propagate data quality rules; (ii) using data lineage to transform data quality rules; (iii) using ETL analysis to determine a set of related assets; (iv) using data lineage graph analysis to determine a set of related assets; (v) modifying a set of related assets; (vi) modifying a set of governance rules; and/or (vii) determining a set of governance rules for a business.
[0066] Some embodiments of the present invention may include one, or more, of the following features, characteristics, and/or advantages: (i) maintaining a data lineage graph; (ii) maintaining a data lineage graph that identifies a set of related data assets; (iii) identifying a set of related data assets based on an upstream process; (iv) identifying a set of related data assets based on a downstream process; (v) applying a governance rule to a related data asset; (vi) applying a transformed governance rule (sometimes also called a modified governance rule) to a related data asset; (vii) determining a set of governance rules for a set of related assets; and/or (viii) determining a set of governance rules for a set of related assets, wherein each asset in the set of related assets is related to each other asset in the set of related assets.

IV. DEFINITIONS

[0067] “Present invention” does not create an absolute indication and/or implication that the described subject matter is covered by the initial set of claims, as filed, by any as-amended set of claims drafted during prosecution, and/or by the final set of claims allowed through patent prosecution and included in the issued patent. The term “present invention” is used to assist in indicating a portion or multiple portions of the disclosure that might possibly include an advancement or multiple advancements over the state of the art. This understanding of the term “present invention” and the indications and/or implications thereof are tentative and provisional and are subject to change during the course of patent prosecution as relevant information is developed and as the claims may be amended.
[0068] “Embodiment,” see the definition for “present invention.”
[0069] “And/or” is the inclusive disjunction, also known as the logical disjunction and commonly known as the “inclusive or.” For example, the phrase “A, B, and/or C,” means that at least one of A or B or C is true; and “A, B, and/or C” is only false if each of A and B and C is false.
[0070] A “set of” items means there exists one or more items; there must exist at least one item, but there can also be two, three, or more items. A “subset of” items means there exists one or more items within a grouping of items that contain a common characteristic.
[0071] A “plurality of” items means there exists at more than one item; there must exist at least two items, but there can also be three, four, or more items.
[0072] “Includes” and any variants (e.g., including, include, etc.) means, unless explicitly noted otherwise, “includes, but is not necessarily limited to.”
[0073] A “user” or a “subscriber” includes, but is not necessarily limited to: (i) a single individual human; (ii) an artificial intelligence entity with sufficient intelligence to act in the place of a single individual human or more than one human; (iii) a business entity for which actions are being taken by a single individual human or more than one human; and/or (iv) a combination of any one or more related “users” or “subscribers” acting as a single “user” or “subscriber.”
[0074] The terms “receive,” “provide,” “send,” “input,” “output,” and “report” should not be taken to indicate or imply, unless otherwise explicitly specified: (i) any particular degree of directness with respect to the relationship between an object and a subject; and/or (ii) a presence or absence of a set of intermediate components, intermediate actions, and/or things interposed between an object and a subject.
[0075] A “module” is any set of hardware, firmware, and/or software that operatively works to do a function, without regard to whether the module is: (i) in a single local proximity; (ii) distributed over a wide area; (iii) in a single proximity within a larger piece of software code; (iv) located within a single piece of software code; (v) located in a single storage device, memory, or medium; (vi) mechanically connected; (vii) electrically connected; and/or (viii) connected in data communication. A “sub-module” is a “module” within a “module.”
[0076] A “computer” is any device with significant data processing and/or machine readable instruction reading capabilities including, but not necessarily limited to: desktop computers; mainframe computers; laptop computers; field-programmable gate array (FPGA) based devices; smart phones; personal digital assistants (PDAs); body-mounted or inserted computers; embedded device style computers; and/or application-specific integrated circuit (ASIC) based devices.
[0077] “Electrically connected” means either indirectly electrically connected such that intervening elements are present or directly electrically connected. An “electrical connection” may include, but need not be limited to, elements such as capacitors, inductors, transformers, vacuum tubes, and the like.
[0078] “Mechanically connected” means either indirect mechanical connections made through intermediate components or direct mechanical connections. “Mechanically connected” includes rigid mechanical connections as well as mechanical connection that allows for relative motion between the mechanically connected components. “Mechanically connected” includes, but is not limited to: welded connections; solder connections; connections by fasteners (e.g., nails, bolts, screws, nuts, hook-and-loop fasteners, knots, rivets, quick-release connections, latches, and/or magnetic connections); force fit connections; friction fit connections; connections secured by engagement caused by gravitational forces; pivoting or rotatable connections; and/or slidable mechanical connections.
[0079] A “data communication” includes, but is not necessarily limited to, any sort of data communication scheme now known or to be developed in the future. “Data communications” include, but are not necessarily limited to: wireless communication; wired communication; and/or communication routes that have wireless and wired portions. A “data communication” is not necessarily limited to: (i) direct data communication; (ii) indirect data communication; and/or (iii) data communication where the format, packetization status, medium, encryption status, and/or protocol remains constant over the entire course of the data communication.
[0080] The phrase “without substantial human intervention” means a process that occurs automatically (often by operation of machine logic, such as software) with little or no human input. Some examples that involve “no substantial human intervention” include: (i) a computer is performing complex processing and a human switches the computer to an alternative power supply due to an outage of grid power so that processing continues uninterrupted; (ii) a computer is about to perform resource intensive processing and a human confirms that the resource-intensive processing should indeed be undertaken (in this case, the process of confirmation, considered in isolation, is with substantial human intervention, but the resource intensive processing does not include any substantial human intervention, notwithstanding the simple yes-no style confirmation required to be made by a human); and (iii) using machine logic, a computer has made a weighty decision (for example, a decision to ground all airplanes in anticipation of bad weather), but, before implementing the weighty decision the computer must obtain simple yes-no style confirmation from a human source.
[0081] “Automatically” means “without any human intervention.”
[0082] The term “real time” includes any time frame of sufficiently short duration as to provide reasonable response time for information processing as described. Additionally, the term “real time” includes what is commonly termed “near real time,” generally any time frame of sufficiently short duration as to provide reasonable response time for on-demand information processing as described (e.g., within a portion of a second or within a few seconds). These terms, while difficult to precisely define, are well understood by those skilled in the art.
(57)

Claims

1. A method comprising:

displaying a plurality of data assets from a data asset storage as a data lineage graph;
determining a first relationship between a first data asset in the plurality of data assets and a second data asset in the plurality of data assets is a direct-read relationship;
determining a first governance rule applied to the first data asset, wherein the first governancerule relates to a lookup function;
transforming the first governance rule into a second governance rule based, at least in part, on the first relationship, wherein the second governance rule relates to a pivot function;
applying the second governance rule to the second data asset;
determining a second relationship between the second data asset and a third data asset in the plurality of data assets is an indirect-write relationship;
transforming the second governance rule into a third governance rule based, at least in part, on the second relationship, wherein the third governance rule relates to a merge and join function;
applying the third governance rule to the third data asset;
identifying the first data asset, the second data asset, and the third data asset on the data lineage graph; and
storing the first governance rule, the second governance rule, and the third governance rule to a governance rule storage;
wherein:

at least determining the first relationship between the first data asset and the second data asset is performed by computer software running on computer hardware.
* * * * *

Javier Echeverría’s The Techno-Scientific Revolution translated into English

The below is my translation into English of Javier Echeverría’s book La Revolución Tecnocientífica.

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Prologue

The scientific revolution began in the last decades of the sixteenth century and developed throughout the seventeenth century. Its impellers (Copernicus, Galileo, Harvey, Descartes, Huygens, Leibniz, Newton and many others) radically changed the European conception of the world, breaking with the Aristotelian-scholastic molds that had predominated during the Middle Ages. The change was slow and took place in some European countries (Italy, Holland, Great Britain, France, Germany), spreading little by little to the rest of Europe and North America. It affected only some disciplines (astronomy, mathematics, physics, medicine), which were the vanguard of philosophical and methodological change. Subsequently, the mathematization of knowledge and experimental methodology were reaching other sciences, with the consequent irruption of new theories in chemistry, biology, geology and, finally, in the field of social sciences.

To promote the new natural philosophy, inspired by the Baconian program, new institutions were created (scientific societies, astronomical observatories, laboratories, etc.), around which the emerging scientific communities came together. The Universities opposed the change, except for rare exceptions, originating famous processes and disputes between the defenders of the new scientific methodology and the maintainers of the Aristotelian method and the medieval structure of knowledge. As a result of this long process, modern science was gradually institutionalized, with notable differences according to the countries and disciplines.

Throughout the eighteenth century, scientists found important allies in the drivers of the Industrial Revolution, especially in Britain, where Newtonian science had a wide social diffusion. With the French Revolution and the introduction of compulsory education, the social dissemination of scientific knowledge was progressively guaranteed, while creating a system of reproduction of emerging scientific communities. During the nineteenth century other European countries followed the French example, with which science was inserted into the European educational system, culminating the scientific revolution. The Humboldt University in Germany and the French Polytechnique became role models throughout the continent.

The first industrial revolution occurred in Britain. Its social, economic and political impact was enormous in Europe. One of its main motors was technology. Science only had an indirect influence on industrial development. Both revolutions, scientific and industrial, have been constitutive of the Modern Era, together with the profound political changes that led to the establishment of democratic forms of government in some European countries, as well as in the United States of America. During the Second Industrial Revolution, the alliance between industry, technology and science was consolidated in some countries (Great Britain, Germany, to a lesser extent France), generating two new professions, that of scientist and that of engineer. Throughout the nineteenth century science and technology interacted closely, with mutual benefits, even forming part of clearly differentiated professional sectors. Scientists began to show that their knowledge could be very useful for industry and for war. The countries that promoted the collaboration between science, technology and industry, became great powers throughout the nineteenth century, to the detriment of ancient powers (Spain, Portugal, Turkey) that did not give way to the new scientific-industrial society.

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Taking as reference these two great revolutions of the Modern Era 1, in this book we are going to analyze a change no less important, the techno-scientific revolution, which implies a new way of doing science. It began in the USA at the time of the Second World War, was consolidated with the Cold War and, subsequently, it has been extended to other countries, particularly in Europe, Japan and Canada. We will focus on the US, since, just as modern science was a European creation, contemporary technoscience has a strong North American imprint. We will distinguish three stages. In the first (1940-1965), macro science (Big Science) emerges, which we will consider as the first technoscience modality. Basic research played a fundamental role as an engine of macro science, especially in the field of physics, but also in chemistry and mathematics. After a decade of crisis and stagnation (1966-1976), caused by the American failure in the Vietnam War and by the broad social response that arose in the US and Europe against the militarized macro-science (May 1968), in the The last quarter of the century saw the emergence of technoscience proper, driven by some large companies, rather than by the States, and focused on the development of new technologies. Technoscience also comes from the USA, although it has expanded rapidly in other countries. The Soviet Union was not able to make the new leap, due to lack of financial capacity and business network. If we consider macro-science and technoscience as the first and second techno-scientific revolution, respectively, it can be said that the current military, economic, political, diplomatic and commercial predominance of the US comes, among other reasons, from its techno-scientific leadership.

Science has not disappeared. Scientific societies and academic science continue to exist. However, its two new offshoots, the macroscience and the technoscience, manifest an enormous push, to the point that some authors tend to think that, nowadays, everything is technoscience. We will try to show that this is not the case, specifying the differences between science and macro science, first (chapter 1), and science and technoscience (chapter 2). The techno-scientific revolution differs in fundamental aspects from the scientific revolutions of which Kuhn spoke, which is why we will dedicate chapter 3 to clarify those differences. More than knowledge, it transforms the scientific-technological practice, generating a new structure, the national system elucidate two basic concepts: techno-scientific systems and techno-scientific actions. Faced with the scientific revolution of the seventeenth century, which modified the structure of knowledge, the techno-scientific revolution of the twentieth century has transformed, above all, the structure of scientific-technological practice. In particular, the value systems that guide scientific activity have changed, which is why we will devote chapter 5 to the axiology of technoscience. It is not the only possible philosophical approach, but to our knowledge it is one of the clearest and most promising. The values of technoscience are much broader and more complex than those of modern science. Conflicts of values are a structural component of technoscience.

The techno-scientific revolution has not only changed the sciences and technologies. In addition, it has contributed to generate a great economic and social change, the information revolution, which began in the last decades of the twentieth century and which, predictably, will continue to develop during the twenty-first century. The link between technoscience and the emerging information society is very close, so that this alliance can be compared with that which modern science and technology maintained with the industrial revolution. These two new revolutions do not originate in Europe, but in the US of America, which has become a hegemonic power all over the world, in part because of its strong support for technoscience. Just as modern science was European, technoscience is American, just like the information revolution. At the moment both revolutions are expanding in other countries. In doing so, different versions of technoscience arise, depending on the diverse cultures in which it is inserted. It must be said that the First World is formed by those countries where these two new revolutions have been consolidated, or are in an advanced stage of development. To the modern concept of industrial, scientific and technological development, we must add the contemporary notion of techno-scientific and informational development. A country can be a scientific and industrial power, and yet be underdeveloped from the techno-scientific and informational point of view. That is why we understand that technoscience is one of the great challenges of the 21st century.

The new modes of production of wealth and knowledge have radically modified power relations and the distribution of wealth in countries, regions and companies. Military power, for example, requires a high techno-scientific and informational development. It is worth bearing in mind that technoscience not only serves to create, discover, invent and build, but also to annihilate and destroy. The links between technoscience and military institutions have been and continue to be very close, and this from the origin of macro-science. Human beings have developed countless war conflicts throughout history, but the Second World War and the subsequent contests in which the US has participated (Korea, Cold War, Vietnam, Persian Gulf, Kosovo, Afghanistan …) they represent a radical novelty: technoscience is a necessary condition for military victory. For many soldiers and a lot of bravery that is possessed, the defeat of war is guaranteed if you do not have adequate techno-scientific development. The same applies to the business sector, especially in the era of globalization. In summary, technoscience is a condition of possibility of economic and military power, which is why the most powerful countries are those with a high level of techno-scientific and informational development. Curiosity and the search for knowledge could be at the base of the emergence of modern science. Instead, the struggle for power is the engine of contemporary technoscience. Therefore we will finish this work with a reflection on technoscience and power.s of science and technology (SCyT), of which we will deal briefly in chapter 4, focusing on the North American system, which is still the canonical . Although the development of technoscience has generated new scientific theories and great discoveries, the basic paradigms continue to subsist in physics, chemistry, biology and mathematics. We are not facing an epistemological or methodological revolution, although there have been great changes in knowledge and scientific methods, but before a praxeological revolution. Therefore, we will try to analyze the new structure of scientific-technological practice, which is the most marked feature of the techno-scientific revolution. For this we will try The revolution of modern science has been widely studied by historians, sociologists and philosophers. The history, philosophy and sociology of science were established in the early twentieth century and focused on the study of modern science, including the scientific revolutions of the nineteenth and early twentieth centuries: chemistry (periodic table, organic chemistry), mathematics (Analysis, non-Euclidean geometries, set theory), biology (Darwin, Mendel), Geology (Lyell) and Physics (Einstein, quantum theory). The philosophy of science, which is the starting point of this work, has been primarily logic, epistemology and methodology of science. For this reason he has dealt with the analysis and reconstruction of scientific knowledge, focusing on the concepts, laws, facts and theories, establishing the theoretical / observational distinction, highlighting the logical-linguistic aspects of knowledge and developing enunciative conceptions of the scientific method, both logical- deductive as logical-inductive and statistics. Without underestimating this meta-theory of science, which has made great contributions to the study of science, we think it is insufficient to address technoscience. Since science has changed, becoming technoscience, the philosophy of science has to modify its approaches considerably, becoming the philosophy of technoscience. For that, it has to focus more on scientific activity than on knowledge, developing a theory of scientific action and paying much more attention to technology. The main purpose of this book is to take steps in that direction, without forgetting the starting point, but addressing a new object of reflection, technoscience, which differs in many and very relevant aspects of modern science and technology. What we say about the philosophy of science is also valid for other studies in science and technology, that is to say for history, sociology, glue, psychology, anthropology, politics or economics of science and technology, although here let’s not deal with those issues. If science has changed, as we will keep in these pages, science and technology studies will also have to change, paying more attention to the science of the 20th century, which is already history, although largely unmade. For this reason we will limit ourselves to a period of time, the post-Second World War, and to a country, the USA, which is where technoscience arose. It is certain that the investigation of the development of macro-science and technoscience in the USSR, in Europe, in Japan and in other countries will provide important clarifications to the theses that we are going to affirm here. Even so, we hope that this first foray into the philosophy of technoscience of the 20th century can contribute something to the studies of science, technology and society, not only to the philosophy of science. Together, it is about developing technoscience, philosophical, sociological, historical, pedagogical or other studies, including scientific studies on technoscience (scientometrics, technoscientific development indicators, etc.). The CTS studies (Science, Technology and Society) constitute the scope where all these perspectives can converge and interact.

We will stick first of all to the axiological questions, because they complete the classical epistemological and methodological studies, and because the Axiology of Science and Technology is much less developed. In summary, in this book we will expose the following theses:

1.- Throughout the twentieth century, and especially since the Second World War, has appeared and has consolidated a new form of science, technoscience or megaciencia (Big Science) 2. Initially we will use both expressions as synonymous, although later we will establish differential nuances between both.

2.- This change is important enough so that we can compare it with the modern scientific revolution. That is why we will talk about a techno-scientific revolution, or rather, techno-scientific revolutions, since they occur in almost all scientific disciplines, although in different ways in each.

3.- The techno-scientific revolution is one of the main engines, although not the only one, of a deeper social and economic change, the informational revolution, which due to its relevance can be compared to the industrial revolution. Put succinctly: just as science was vital for the development of industrial society, so technoscience is a basic component of the information society.

4.- The various studies on science and technology (historical, philosophical, sociological, political, cultural, anthropological, economic, etc.) have to face the challenge raised by the techno-scientific revolution, giving rise to the studies of technoscience. This trend is already evident in the last years of the twentieth century, characterized by a profound transformation of transdisciplinary studies of science and technology.

5.- In the case of the philosophy of science and technology, the perspective from which this book is written, it is necessary to deal primarily with the philosophical analysis of techno-scientific activity, instead of focusing on scientific knowledge or technological artifacts, as philosophy of science and the philosophy of technology have traditionally done. Accordingly, we will make some first proposals to analyze the structure of the techno-scientific activity. For this we will study the moment that, generally, is considered foundational of the macrociencia, that is to say the report of Vannevar Bush (1945), in which the technological scientific system was designed that allowed the consolidation of the technoscience in the USA, and later in other industrially, technologically and scientifically developed countries.

6 .- The philosophy of science of the twentieth century devoted many efforts to justify scientific knowledge, its objectivity and rationality. One of the ways that followed for this was the search for the foundations of science. It was understood that, since science was knowledge, these foundations (principles, laws, logical structure of the theories, empirical basis, facts) should also be knowledge, or at most a methodology to obtain valid knowledge. In our opinion, this way is inadequate to investigate the foundations of technoscience. The traditional philosophical problem of the justification of scientific knowledge is superimposed on another question, perhaps more important: the validation of scientific practice.

7.- Finally, and continuing the line followed in recent publications 3, we will first of all deal with the values of technoscience (chapter 5), as it is one of the areas where the techno-scientific revolution has the greatest impact. Faced with the axiological neutrality of the positivist tradition and the restriction of epistemic values or values internal to science (Laudan), we will affirm and develop the thesis of the axiological pluralism of technoscience, which includes the assumption of continued axiological conflicts in technoscientific activity . To analyze the values of technoscience in its various contexts and situations, we will use two formal instruments, the evaluation matrices and the evaluation thresholds or thresholds. In chapter 5 we will show that the Science and technology indicators that are commonly used in science policy are modalities of such matrices, as well as the various evaluation protocols that are used in daily techno-scientific practice. Axiology provides a powerful analytical tool that brings together and integrates in the same conceptual framework the various tools used today to assess techno-scientific actions and their results. This will be the most significant practical contribution of this work.

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The ideas developed in this book are the result of various seminars, courses, conferences and debates in which the author has participated in recent years. The facilities received from the Institute of Philosophy of the CSIC, and in particular from its Director, José María González, allowed me to find some time to clean up multiple drafts and organize this set of ideas, suggestions and proposals. The financial support of the Ministry of Science and Technology (Projects PB 98-0495-C08-01 and BFF2002- 04454-C10-01) made possible the organization of several of these seminars and conferences, in which I had the opportunity to contrast the initial theses and to improve them, thanks to the multiple criticisms received, which I deeply appreciate. Francisco Alvarez and Armando Menéndez were the ones who most closely collaborated with me, although many other people made contributions of great interest: Adelaida Ambrogi, Roberto R. Aramayo, Fernando Broncano, José Antonio Díez Calzada, Anna Estany, José Luis Falguera, José Ferreirós, Amparo Gómez, Marta González, José Luis González Quirós, Mercedes Iglesias, Carlos López Beltrán, José Antonio López Cerezo, José Luis Luján, Sergio Martínez, Javier Moscoso, Emilio Muñoz, León Olivé, Javier Ordóñez, Francisco Pérez, Ana Rosa Pérez Ransanz, Eulalia Pérez Sedeño, Miguel Angel Quintanilla, Ana Rioja, Concha Roldán, Frenando Sáez Vacas, Jesús Sánchez, José Manuel Sánchez Ron, María Jesús Santesmases, Juan Vázquez, Jesús Vega, Ambrosio Velasco and Jesús Zamora Bonilla, among others. The Associated Unit between the University of the Basque Country and the CSIC, which co-directed with Andoni Ibarra, was another of the forums where these proposals were discussed, as well as the Associated Unit between the University of Seville and the CSIC, co-directed by Ramón Queraltó. This book would not have been possible without the strong support given to its publication by María Luisa Capela and Héctor Subirats as the former heads of the FCE team in Spain, as well as its successors, Ricardo Navarro and Juan Guillermo López, who had to suffer some delay in the delivery of the original. But those who had more patience with me were Belén and Irene, already in the domestic sphere, where the computer was on for too long in recent months.

To all of them my sincere thanks.

J.E. January 2003

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Chapter I

Sciences, macro-sciences and technosciences

I.1: Microscience and macroscience.

Derek J. de Solla Price, physicist and historian of science, gave Pegram conferences in 1962 at the Brookhaven National Laboratory, one of the most important in the US for the peaceful application of nuclear energy. In them, it was proposed to introduce a quantitative methodology for the study of science. “Why not apply the resources of science to science itself? Why not measure and generalize, hypothesize and draw conclusions? “- he asked at the beginning 4. According to his physics training, Solla Price was interested in the size and shape of science, instead of focusing on the contents , theories and discoveries, as philosophers and historians of science had done since the beginning of the 20th century. “Considering science as a measurable entity,” he said, “I will try to calculate scientific personnel, literature, talent and expenditures on a national and international scale.” 5 These magnitudes are nowadays called indicators of scientific development and are of great importance to guide scientific policies. This line of inquiry generated a new discipline, Scientometrics (Scientometrics), which has had great development in the second half of the twentieth century and is part of the quantitative studies on science and technology.

The data presented by Solla Price, all of them referred to the USA, allowed him to affirm that science had grown exponentially in size during the 20th century. This increase affected the number of scientists, publications, novelties and discoveries achieved and also the financing of scientific activity. To give an example, in the 60s lived 80-90% of the scientists that had never been in history. This vertiginous growth led him to propose the hypothesis that science had entered a new phase, the Great Science or macro science (Big Science). He characterized it by means of two mathematical laws, both conjectural and subject to empirical testing: the law of exponential growth and the law of saturation. The first stated that “science grows at compound interest, multiplying by a certain amount in equal periods of time” 6. The period of doubling the size of science fixed it at 15 years. The second law qualified exponentiality and proposed as a growth model the logistic curve, according to which exponential growth with duplication every 15 years is only the beginning of a logistics curve, which subsequently reaches a ceiling or line of saturation. From this height growth can stagnate, in which case science will enter a phase of senility, or it can recover the exponential rhythm, entering a new phase of accelerated growth 7. Forty years later, there is no doubt that the Second hypothesis has been the right one.

The data and the mathematical models proposed by Solla Price have been corrected and further refined by the experts in Scientometrics, but to a large extent they are still valid. From a philosophical perspective, what matters is that the law of exponential growth led him to propose a conceptual distinction that has had great acceptance among scientists: on the one hand there would be Small Science (XVII, XVIII and XIX centuries) and on the other the Great Science (twentieth century). Both are distinguished by their rate of growth, very slow in the first case, very fast in the second. It is appropriate to consider whether this distinction between two types of science is justified philosophically and, above all, whether the differences in size and rate of growth are sufficient reason to introduce such an important conceptual distinction and whether this is purely quantitative, or qualitative as well.

The notion of macroscience (Big Science) had been suggested the previous year by Alvin Weinberg, who had suggested an economic criterion to define it: for a project to be considered as macro-scientific it is necessary that its realization requires a significant part of the gross domestic product (GDP ) of a country 8. According to Weinberg’s criterion, the distinction between science and macroscience is primarily budgetary 9. Solla Price accepted this economic criterion, but wanted to clarify and formalize it. For this he proposed a mathematical model that justified the need to significantly increase the financing of science. The conceptual distinction that he introduced affirmed that scientific research had entered a new historical stage, reason for which the problem of its financing had to be reconsidered: “the science of today overflows so widely the previous one, that it is evident that we have entered into a new era that has swept everything away, except for the basic scientific traditions “10. Finally, Solla Price suggested that his research was only a first step:” if we are to characterize the current phase as something new, different from the bourgeois science common to Maxwell, Franklin and Newton, we can not base ourselves solely on a growth rate “11. It left open the way to distinguish the macro-science from science not only by its size, but also by qualitative and cultural criteria.

The question was taken up in a Symposium organized by Stanford University in 1988, whose Minutes have been edited by two historians of science, Peter Galison and Bruce Hevly. For Hevly, “macro science is not science made with large or expensive instruments” 12. High budgets and large instruments are indicators of change, but according to Hevly, macro-science was characterized from the beginning by 13:

a): The concentration of resources in a very limited number of research centers.

b): The specialization of the work force in the laboratories.

c): The development of relevant projects from the social and political point of view, which contribute to increase the military power, industrial potential, health or prestige of a country.

In this Symposium, the problem of the origin of the macroscience, as well as its subsequent evolution, was also discussed. Hevly himself pointed out other peculiarities of macro-science, which have been manifesting throughout his later evolution 14:

d): The relationship between science and technology has taken new forms, which have influenced the nature of both.

e): Macro-science requires interaction between scientists, engineers and the military. Galison confirmed this point, stating bluntly that “it is manifestly impossible to examine the great science without taking into account the science of war” 15.

Other authors also presented other proposals to characterize macroscience. Robert W. Smith, for example, recalled that “among the characteristics that have been identified in the great science are politicization, bureaucratization, high risk and loss of autonomy.” 16 Galison said that mega-science has many faces, what his inquiry is difficult and complex. All the analysts pointed out that the discontinuity between small and large science is partly fictitious, which does not prevent the convenience of maintaining that distinction. Panofsky, one of the great promoters of the Great Science at Stanford University (MARK III project), said that “there is no conflict between the small and the great science, and in fact there is a continuum of scale between the different activities” 17 With this, I went back to the initial theses of Solla Price, insisting that the transition from science to megacience was evolutionary, not revolutionary.

There were no shortage of authors who investigated the emergence of mega-science in Europe (CERN) or in Japan (Tsukuba Science City), showing that there are important cultural differences in their development according to countries and disciplines. In summary, both participants in the Stanford Symposium and other authors who have addressed this issue, agree when using the term “macro-science” to refer to a new stage of the development of science, but differ from each other to the time to try to specify it and define it. Most scholars would subscribe to the statement of Sánchez Ron, according to which “the Great Science is a research procedure characteristic of our century” 18, referring to the twentieth century. But on the notes that define the Great Science, the positions are very diverse. We infer from all of this that it is worth specifying conceptually the differences between science and megaciencia and we opt for a philosophical perspective for it. Not in vain philosophy has strived to elucidate the concepts throughout its history.

Throughout this work we will maintain that throughout the twentieth century not only the size and rate of growth of science have changed, but something much deeper, namely: the structure of techno-scientific activity. The economic characterization of Weinberg and the quantitative models of Solla Price are indicators of this change, but they are not its cause. The emergence of megaciencia implied a deep change in the scientific practice, from which many other changes are derived, some of great magnitude. Therefore, we will also maintain the thesis that throughout of the twentieth century there has been a profound revolution in science and technology: a techno-scientific revolution. Since, when talking about scientific revolutions, the work of Thomas Kuhn is an obligatory reference, we will not only deal with distinguishing science from macro-science and technoscience (chapter 1), but we will also analyze the notion of “techno-scientific revolution”, distinguishing it from the Kuhnian scientific revolutions (chapter 2). Put succinctly, the scientific revolutions that Kuhn studied (Copernicus, Galileo, Newton, Lyell, Lavoisier, Einstein, quantum mechanics, etc.) transformed the structure of scientific knowledge first of all. The techno-scientific revolution of the twentieth century, on the other hand, is based on a radical change in the structure of scientific activity, and therefore has many facets to analyze, including the changes in theory that derived from it. This change in structure brought with it an increase in the size of science, but it also modified the objectives of science, the scientific communities, the modes of organization of research and the criteria for assessing results. In particular, it produced a profound symbiosis between science and technology. We will also maintain that, after the emergence of the macro-science, the progressive entrepreneurization and computerization of the research activity generated in turn a new qualitative change, which has manifested itself especially in the last quarter of the 20th century. Therefore we will say that the macroscience was a prelude to technoscience, or if you want a phase of transition. Philosophically speaking, the great change experienced by science in the 20th century is better analyzed if we speak of technoscience than of macroscience. For this reason, we will consider macroscience as the first technoscience modality.

I.2: The origin of macro-science.

By hypothesis, Solla Price accepted that “the cataclysmic changes associated with the Second World War were the ones that initiated the new era and caused all the important differences (between the Small and the Great Science)” 19. Thus, it placed the beginning of macro-science at the time of the Second World War, even accepting that the transition from the Small to the Great Science was gradual 20.

Galison, Sánchez Ron and Seidel, among others, have pointed out the historical importance of the design and construction in Berkeley of the first cyclotron by Lawrence (1932) 21. Consequently, they tend to date the beginning of the Great Science in the previous decade. to World War II 22. Indeed, Lawrence’s project is a good example of a macro-scientific proposal, although it should not be forgotten that large cyclotrons and particle accelerators were built after 1940. But, from our point of view, the debate about the specific moment in which the megacience arose is vain. We are not facing a discovery that could be attributed to a specific person, nor dated and located at a specific time and place, 23 but rather to a change in the structure of scientific activity, which required a broad lapse of time to emerge, consolidate and develop. The techno-scientific revolution was not made by a person or a Research Center. Nor was it an epistemological, methodological or theoretical change, in the manner of the scientific revolution of the seventeenth century. It was a radical transformation of the research activity that took place in several research centers at the same time, although in some it crystallized with greater speed and clarity of ideas. What is more, not only occurred in laboratories and research centers, but also in other scenarios (scientific policy offices, companies, foundations, strategic study centers, etc.). On the other hand, the emergence of technoscience not only affected research, but also the management, application, evaluation, development and dissemination of science, that is, scientific activity as a whole. The techno-scientific revolution was a protracted and complex process, which is still happening now, as technoscience continues to expand in different countries. In each of them adopted different modalities, as in the various disciplines. But even so, there are a series of common features that allow us to characterize the new structure of scientific-technological practice, as we will see below.

Let’s go by steps, going back to the first technoscience modality, that is, to Big Science. The megaciencia brought with it a new scientific-technological system and for that reason the changes in the scientific practice were numerous and important. Some North American universities and research centers (MIT, Berkeley, etc.) had pointed in that direction in the 1930s. That is why we can speak of several examples of mega-science prior to the Second World War, such as the Radiation Laboratory of MIT, the Klystron Stanford Laboratory or the Radiation Laboratory of Berkeley. However, the greatest rise of these research centers occurred during the war and in the years immediately after. What these pioneering centers pointed out in the 1930s showed its enormous effectiveness during the World War. The report by Vannevar Bush, Science, the Endless Frontier (1945) provided a theory for this change, enabling the establishment of a new system of science and technology in the US after World War II. This CyT system (SCyT) was consolidated in the postwar period and became widespread in the 50s, first in the US, and later in other countries, with the corresponding variants and specificities.

Therefore, we will place the beginning of the megaciencia at the time of the Second World War, underlining that it occurred in the US of America and in the field of militarized physical-mathematics, as shown by the four great projects that we consider as initial canons of the Great Science: the Radiation Laboratory of Berkeley, the Radiation Laboratory of MIT, the ENIAC project of the Moore School of Pennsylvania and, above all, the Manhattan Project (Los Alamos), an authentic paradigm of macro science, which led to the manufacture of the first atomic bombs 24. Other countries (Germany, Great Britain) developed similar projects in World War II, and even before 25. But during the postwar period they lacked economic resources and enough political support to boost technoscience. These countries prioritized reconstruction, rather than creating a national science and technology system that would lead them to world leadership in the postwar era, as the USA did. In the American case, emerging technoscience contributed decisively to its military victory. But the key decision was to promote the new organizational structure of megaciencia during the postwar period, using important public funds for it. After the war, the only country that was in economic, political and military conditions to develop the Great Science was the USA. Therefore, megaciencia arises in the four aforementioned centers (and in others that could be mentioned), but the new structuring of scientific activity only takes place after 1945, more specifically with the approval of the Bush report and its progressive implementation. functioning.

Some years later the USSR became a nuclear power, developed its own SCyT system and, for example, took the initiative in space exploration with the launch of the first artificial satellite, Sputnik (1957). Therefore, Big Science also developed in the Soviet Union, but later. The scientific-technological competition between the two great military powers was one of the most significant characteristics of the Cold War and was closely linked to its military, political, industrial and ideological rivalry. The competition for the dominance of space between the US and the USSR in the 50s and 60s is an excellent example of megaciencia, as well as the hard emulation between the National Laboratory of Brookhaven and the European CERN (1952) in the field of physics of small particles. After 50, examples of mega-science abound, and since the 1980s are multiplied by economically developed countries, although with significant differences with respect to the first era of mega-science. The greater presence of private companies and the computerization of techno-scientific activity characterize, among other things, this second era of mega-science, in which what is properly called technoscience is configured. Therefore, we will say that megacience was the precursor of technoscience and that both differ from modern science (Small Science) based on qualitative criteria, not just quantitative ones. The objective of this chapter is to delimit these differential features, which in many cases are a matter of degree or scale, but in general they are deeper.

We will start from the Solla Price hypothesis: the new form of scientific activity was first configured in the USA in the 40s. Apart from the four major projects we have mentioned, a key moment is the Vannevar Bush Report on politics (Science, the Endless Frontier, 1945), which will be discussed in more detail in chapter 4. The report stated that basic research is the engine of technological innovation and that this, with the help of industry and State agencies, is a necessary condition for the economic and social progress of a country, as well as for national security. Scientific research was no longer justified by the search for truth or by the domination of nature. These objectives, which characterized the emergence of modern science and technology, continued to exist, but new ones emerged, much more specific to technoscience. In particular, it was about guaranteeing the military, political, economic and commercial predominance of a country. Throughout this work we will maintain the thesis that technoscience is characterized above all by the emergence, consolidation and stable development of a scientific-technological system that gives a place to a new mode of knowledge production. Unlike the First World War, after its conclusion it turned to normal scientific and technological activity, the Bush report designed a new scientific-technological system that could be worth as much for peace as for war 26. Among other aspects, Technoscience is characterized by the instrumentalization of scientific-technological knowledge. The advance in knowledge ceases to be an end in itself to become a means for other purposes.

I.3: Macro-science and technoscience.

The distinction between Small Science and Great Science can be improved if the term “technoscience” is used and Big Science is considered to be the first historical modality of technoscience, followed by others, for whose identification it is necessary to resort to other criteria, apart from those of size and growth proposed by Solla Price.

We will accept the proposals of Weinberg, Hevly, Galison and Smith, but we will try to better organize the system of distinctive features between science and technoscience. Technoscience, for example, not only modifies science: it also transforms technological, industrial and military activity, thanks to the development of a national system of science and technology that transcends the limits of scientific communities and generates techno-scientific companies, superimposed on communities pre-existing scientific The indicators proposed by Weinberg and Solla Price, as well as the criteria used by Heavy, Galison, Smith and others, are not enough to fully explore the concept of “technoscience”. For our part, we will characterize it through a set of distinctive features, in order to introduce a minimum of philosophical rigor, which we miss in a large part of the historical studies on macro-science. It is necessary to carry out a detailed conceptual analysis and from various perspectives to properly distinguish between science, macroscience and technoscience. The economic, scientometric and sociological criteria establish some differences, but they are not enough.

We will start with the first technoscience modality, that is, with the macroscience. This is characterized by the following distinctive features:

(a): Government financing.

The Federal Government of the USA decided to promote basic research, actively involved in the promotion of science, all in order to significantly increase the military and commercial power of the US. Thus broke a tradition of federal non-intervention in scientific affairs, which had been maintained during the nineteenth century and early twentieth century. Scientific research was the exclusive responsibility of academic institutions, although it was usually financed by patrons, foundations, some States of the Union and some companies very companies. In general, the interest of the companies was oriented almost exclusively to applied research, in accordance with the traditions of North American industrialization. At the time of the Second World War there was a great change in the USA and military agencies, political committees and government offices appeared, such as the Office of Scientific and Technological Mobilization, which began to strongly boost research. This brought about the entry of new and powerful agents in the field of knowledge, until then practically monopolized by the scientific communities. For this, large equipment and research macroprojects were financed, something that was beyond the reach of the economic means of the universities and research centers, with rare exceptions. Macro-science emerged around a few centers and projects (Berkeley, MIT, Moore School, Los Alamos, etc.), all of them with strong military or political support. The great military needs aroused by the Second World War were decisive at the time of increase the size of the projects and the means of financing. As far as basic research is concerned, the US lagged behind Germany and other European countries. The aim was to correct this delay in a few years, signing up for it the best European scientists, many of them with difficulties in their countries of origin due to the rise of Nazism and fascism. Faced with the traditional patronage of the Foundations or the States, the Federal Government and the Military Agencies decided to invest heavily in basic research, provided that it was closely linked to the lines that the new agents considered strategic.

(b): Integration of scientists and technologists.

For the development of these macroprojects, large equipment and investments were required, as well as large and multidisciplinary research teams. This required the collaboration (not free of internal conflicts) among scientists, engineers, technicians and research funders. A scientific macroproject not only pursues objectives linked to the search for scientific knowledge. It also aims to generate advances and improvements in the available technologies, so that these would be useful to the financing institutions, and in particular the Army, Navy and Aviation. Therefore, macro science requires that engineers and scientists collaborate closely if they want to achieve their respective objectives, breaking the previous disciplinary separation.

(c): Social contract of science.

The USA reorganized its Agencies and research centers, hiring scientists, engineers and technicians of great prestige for it. At the same time, they subcontracted with some academic institutions and with large industrial companies the realization of a good part of these macroprojects, provided that scientists, institutions and companies offered a high degree of confidence, reliability, scientific competence and industrial efficiency. Scientific research became part of an R & D industry. Each scientist and engineer had to contribute their knowledge and skills to a joint project that was developed by previously designed and planned stages. The management of these projects had a fundamental role, because they knew the final objectives, fixed the development phases and the intermediate objectives, maintained the relationships with the financing agents and potential clients, managed the available human and material resources and signed new contracts with experts and specialized companies when it was necessary for the proper development of certain phases of the project. In summary, the macroscience was not developed solely by laboratories, but by a complex of scientific industries managed and directed according to models of business and military organization. Academic science was superimposed on an industrial, political and military framework that radically modified the organization of research. While maintaining its traditional autonomy in laboratories, part of science was industrialized, that is, it became an auxiliary company of the great scientific-technological projects. As a result of this strategy, what was later called the social contract of science among scientists, engineers, politicians, military and industrial corporations. The report of Vannevar Bush (1945) is usually considered the founding text of said contract. We will analyze its content in greater detail in chapter 4.

(d): Industrialized macro-science.

These changes had direct consequences in the scientific practice, because the laboratories that collaborated in a macroproject of investigation happened to comprise of authentic factories scientists, as it happened in the laboratories that investigated on radars and in the project Manhattan 27. The investigation macrocientífica it requires large laboratories, whose construction has to be carried out by the industries, and whose use is shared by several research teams. It broke with the tradition of academic science, in which institution or scientist had its own laboratory, arising shared equipment. This allowed to optimize the resources, but it forced to coordinate the investigations of different teams and to keep in mind the criteria of people external to the scientific communities. The emergence of the macroscience brought internal conflicts in the scientific communities: some were integrated into the macro-projects of research, but there were many criticisms and resistances. The hard core of the macrociencia concentrated in the offices of direction, where the main decisions were taken. Over time, this led to a bureaucratization of scientific activity, hitherto unknown. The romantic era of scientific research (Darwin, Mendel, Einstein, the Curie spouses, etc.) had ended, entering the stage of industrialized macro-science. Obvious is to say that this transition did not occur everywhere. The Small Science continued to exist, but before it emerged a new mode of knowledge production, which was considered by the political authorities as a priority. Between the academic science that continued practicing in most of the Universities and the industrialized macroscience for which some chose, a border was gradually opened.

(e): Militarized macro-science.

Many of the scientific macroprojects had military support and funding, especially in the early stages of development. Therefore, they were secret, contrary to the tradition of modern science, based on the publication of research results. Faced with the traditional autonomy of scientists when determining what needs to be published, military R & D agencies introduced new values into scientific practice (secrecy, discipline, loyalty, patriotism, etc.). During the world war, a significant number of scientists and engineers was militarized. This phenomenon had occurred in previous armed conflicts. The novelty was to maintain the partial militarization of science during the postwar period. Many of the scientific macroprojects continued to have military funding, both in the Korean War (1950) and, especially, during the Cold War. Although the results of some secret projects (for example, ENIAC-type computers, or radar) were transferred to civil society, the military agencies designed new macro-projects (defense systems, space exploration, nuclear energy, cryptology, etc.) that followed remaining within the scope of militarized macro-science. In this way, some military institutions became stable agents for research scientific and technological 28. Macro-science was not only militarized in its emergency phase, but also, albeit partially, in the later stages of consolidation and development. The science and technology systems of developed countries always include military R & D agencies, serving a significant part of the scientific communities 29.

(f): The scientific policy.

The emergence of macro-science is concomitant with the emergence of scientific-technological policies, public or private. Some prestigious scientists left the laboratories and moved into management and advisory cabinets, becoming experts in the negotiation and design of scientific-technological policies. A new type of scientific-technological action emerged: the design of policies for macro-science. Its main action consisted of organizing the System of Science and Technology (SCyT) and for this they had to access the highest levels of political and military power, also maintaining close ties with large industrial corporations. A macro-scientific company was obliged to join lobbies formed by scientists, technologists, businessmen, the military and politicians. As President Eisenhower pointed out, lobbies formed by scientists, engineers, military men and businessmen had acquired great political power in the US in the 1950s. Macro-scientific companies competed with each other for large projects, which is why their Linkages with the spheres of power was imperative. In summary, the macroscience involved the full connection of science with power (political, military, economic). In particular, some scientists became direct advisers to the White House, acquiring considerable influence.

(g): The macro-scientific agency.

In front of the great “men of science” that made modern science, the macroscience was made by large coordinated teams that integrated their respective knowledge and skills into a common project that had mixed objectives. In philosophical terms it can be said that the subject of macrociencia became plural, breaking with the traditional methodological individualism. Leading the research teams were always people of great scientific prestige, but their role was that of project managers and macro-scientific agencies, rather than researchers in the classical sense of the word. The macroscience is done by legal persons, not by natural persons. Here lies another of the great changes in the structure of scientific activity.

We will return later on this last difference and we will add others, but the six distinctive features that we have just presented can serve for a first characterization of the macroscience. As the new scientific-technological system was consolidated, additional specific features emerged. The macro-science of the 50s ended up becoming technoscience at the end of the 20th century. Public investments in R & D grew continuously until 1966, the date on which there was a major crisis, coinciding with the arrival of the Nixon Administration. With the Presidency of Reagan the social contract of science was renewed and funding grew again, but based on criteria very different from those of the 50s and 60s. In the last quarter of a century we can properly speak of technoscience, not only of macroscience. The a huge increase in private financing will be one of its distinctive features, 30 as we will see in chapter 2.

The previous characterization of the macroscience can be criticized from different perspectives. For example, it can be argued that there are other distinctive features of macroscience that have not been mentioned. Some of the proposed specificities may also be questionable: there are cases in which the private financing of basic financing was very considerable, as we will see in section 2.6. This first system of distinctive features does not suppose more than a first approximation to our research object, which is technoscience. Macro-science is only one of its modalities, historically the first.

There is also a second objection, namely that all those peculiarities that we attribute to macroscience have already manifested themselves earlier in the history of science and technology, even if on a smaller scale. We would also accept this criticism, since, as we will see in section II.3, the attribution of these distinctive features will be a matter of degrees. It is possible to look for multiple historical examples in which the militarization of science had already taken place, its partial conversion into a company, the symbiosis between science and technology, the appearance of new management models and research management, etc. What is decisive is that at the time of the Second World War and in the United States of America all these transformations took place at the same time, and on a previously unknown scale, because of the military conflict. That is why we speak of macro-science: the high degree of realization of the six distinctive features above implies a quantitative change. But, in addition to all this, there was a systemic change: a new science and technology system emerged in the United States. Its progressive consolidation during the postwar period produced a change of structure in the scientific-technological activity. Therefore, it being true that the emergence of technoscience depended on an increase in scale or degree, it is no less true that this set of quantitative transformations generated a structural change, which resulted in the emergence of a new SCyT system. The constitution of the new scientific-technological system was a necessary condition for the emergence of technoscience in the 1980s. Unlike macro-science, the distinction between science and technoscience is not a question of size or scale, as we shall see in the next chapter . The macroscience arose at the same time as the SCyT system. The further development of this SCyT system allowed the progressive appearance of technoscience.

The third possible objection seems less relevant to us. It is possible to affirm that during all this time there were great changes in the scientific knowledge, not only in the scientific-technological practice. This is very true. But we already stated in the prologue that our purpose is to focus on changes in the structure of scientific activity, not on scientific knowledge. Philosophers and historians of science and technology who focus on this second aspect abound. For our part, we have chosen a different and much less studied subject. In the next section we will try to clarify this new perspective of philosophical analysis, opposing our theses to those of the defenders of the teleological conception of scientific rationality.

I.4: The objectives of the macroscience.

When reflecting on scientific rationality, many philosophers have tried to define it in terms of the objectives of science. Such is the case of Popper, Hempel, Lakatos, Goldman, Rescher, Newton-Smith, Levi, Laudan, Giere and many others 31. For Popper, for example, the ultimate goal of science is the search for truth. This was understood as a regulatory ideal, which is never achieved, but which can be approached gradually whenever a falsificationist methodology is used. If a theory has endured numerous and severe refutation attempts and has survived that criticism, we have reason to think that it is more plausible than another that has not been put to the test by the falsificationist methodological imperative. For Lakatos, on the other hand, the rationality of science is justified by the new and surprising facts that it is able to explain, as well as by the increase of its heuristic potentiality. For Laudan, the key to rationality lies in the ability to solve problems, which is why the goal of science is to propose and solve problems. Many other thinkers have defended different variants of this teleological conception of rationality, agreeing that the objectives of science justify their rationality, but then have differed between them when it comes to specifying what those goals or objectives are. For its part, most scientists have had to think that knowledge is a good in itself and that the search for knowledge (valid, contrasted, etc.) is the fundamental goal of scientific research.

The same applies in the case of technology. There have been thinkers who have encrypted technical rationality in the search for maximum efficiency. Others have made it depend on the objective of helping to satisfy human needs or to increase the level of well-being and adaptation to the environment. In both cases, the philosophers of science and technology based both modes of rationality on their respective ultimate goals, considered as internal to science and technology. Whatever they were, science and technology had their own ends, on the basis of which scientific and technological rationality was justified.

With the advent of macro-science, these theories of rationality have to be challenged. By using the Weberian distinction, the ends of science and technology cease to be ultimate values, to become instrumental values. Its achievement is desirable, but above them there are other objectives to be achieved. The Bush report makes this very clear, as we will see in the next chapter. The objectives of the macro-science are not only scientific, nor are they technological. Some of the goals of a scientific macroproject may be the advancement in knowledge, or the invention of more efficient artifacts, but on these objectives, others are the ones that give meaning to the financing and realization of the project: it may be about improving the defensive and offensive capacity of an army, it can be to win a war, you can try to improve the productivity of an industrial sector, or simply increase the prestige of a country, its level of security or its position in international markets. In the Manhattan project, for example, scientists were interested in calculating the critical mass in a nuclear fusion process, which they achieved. But, above them, the designers of the project wanted to have a weapon of mass destruction that could serve to quickly win the war or, later, as a deterrent against future attacks coming from abroad. The industries that collaborated in the project, meanwhile, generated wealth, economic benefits and, where appropriate, jobs.

The same can be said of the ENIAC project and most of the subsequent macro-scientific programs. Von Neumann wanted to design and operationalize a computer that could solve nonlinear problems, which would greatly contribute to the resolution of relevant physical and mathematical problems. Eckert, the project’s chief engineer, was passionate about the technological challenge posed by the construction of a machine capable of solving multiple computational problems. However, the Air Force financing the project was primarily concerned that the ENIAC calculated the trajectories of long-range projectiles with maximum precision and speed and that it simulated with sufficient approximation the processes of fluid dynamics that occur during an explosion. . All managed to meet their objectives, to a greater or lesser degree, but, as in the Manhattan project, the military purposes prevailed over the scientific-technological, both in designing the project and throughout its execution and, of course, to the time to apply the resulting innovations: the computer and the atomic bomb. Similarly, NASA’s space exploration program was carried out for reasons of national prestige in the context of the Cold War, notwithstanding that its realization also entailed important scientific discoveries and undoubted technological advances. The strictly scientific and technological objectives were subordinated in all these cases to the goals of another nature that had been defined by the promoters and financiers of these macro-scientific projects.

We will conclude that the macro-scientific actions have plural objectives, some of which are scientific and technological, others military, business or political. Very often, the latter are the most effective, despite being “external” to the scientific and engineering communities. This implies a continuous tension in the macro-scientific activity, which arises from its own structure, that is, from the diversity and heterogeneity of its objectives, as well as from the frequent subordination of epistemic and technical ends. Sometimes equilibrium points are achieved, so that all leave relatively satisfied, sometimes not. What seldom happens is that the “own” objectives of science or technology are the priority, however much there are scientific policy actions aimed exclusively at satisfying them. 32. The macro-scientific activity is systemic and each of the relevant actions of Scientific policy, including programs for the general promotion of knowledge, only acquires meaning based on the existence of many other scientific-technological policy actions aimed at satisfying other types of objectives, some of them without any publicity and with much greater funding. There are occasions in which the promotion of basic research is a pure adornment or complement of the scientific-technological policy system. Such is the case, for example, of the promotion of research in the field of humanities, with some exceptions, when research acquires strategic value.

Macro-science is not only done by scientists and engineers. These communities are part of a previously designed scientific-technological complex (SCyT system), in which many other agents intervene. All this affects the election and provision of the means to carry out the investigation. A seasoned researcher must be able to argue that, in addition to the scientific achievements of his research, other benefits may be derived, which are the ones that really interest the other agents involved in a system that promotes research, development and innovation. Macro-science is based on a complex network of interprofessional relations, not on the autonomy of scientific communities or on the Individual genius of some people. Faced with the model of instrumental rationality, where the aims of scientific and technological activity were clear and distinct, the goals and objectives of the macro-scientific activity constitute a complex structure, not free of internal and external tensions, because this activity is promoted by a plurality of agents with interests and objectives often found.

In our view, this tension is due to the existence of value conflicts in the macro-scientific activity. The plural subject of macro science guides its actions based on a plurality of values. In the Manhattan project, for example, a physicist could try to achieve properly epistemic objectives and an engineer technological objectives. But the military supported the project because of its enormous strategic importance and the industrialists who collaborated for economic reasons. Politicians, on the other hand, had their own objectives (to minimize their own losses through atomic bombs, to show the power of the US, to win elections, etc.). In order to properly analyze the macroscience, it is necessary to start from the hypothesis that scientific macroprojects are guided by a plurality of values and objectives, not by the search for truth or the increase of efficiency. In some phases values prevail, in others. There are stages in which the scientist or the engineer enjoy full autonomy. In others, however, they must strictly follow what is required of them. An axiological analysis of macroscience can not be monistic, but pluralistic, precisely because the structure of the macro-scientific activity is plural, and that is within the very bosom of the macroscience, not outside it.

1.5: The concept of “technoscience”.

The expression “technoscience” is controversial. Scientists who devote themselves to basic research often look at it with distrust, because it seems to prioritize technology and applied research. The philologists consider it a barbarism, when mixing two lexical roots of Greek and Latin origin. Many philosophers of science prefer to continue establishing clear lines of demarcation between science and technology, fearing that when speaking of technoscience the specificity of science will disappear, being devoured by technology. Others, on the other hand, affirm that technoscience is a reality since the 19th century, and even before 33. Some historians of science, on the other hand, tend to accept this expression 34 and sociologists of science such as Bruno Latour use it as a denomination technique. For our part, we believe that, once clarified conceptually, this expression is essential to try to understand and interpret some of the profound changes that have taken place in the scientific-technological activity over the past century 35.

The term “technoscience” was proposed in 1983 by Bruno Latour, in order to “avoid the endless expression of science and technology” 36. Latour posed the question “who really does science?” And tried to show that science does not only make it scientists, criticizing the internal / external distinction, widely used when reflecting on science. According to that distinction,

– scientists are active in science, that is, researchers, outside of it, politicians, businessmen, professors, lawyers, etc.

– science is done first of all in experimental laboratories and is perfected in congresses and scientific journals, where the scientific community discusses and agrees on the proposals that, coming from the laboratories, it considers acceptable and valid, even if only to conjecture title.

– once elaborated, this knowledge is disseminated to society and applied to solve practical issues. At this moment science generates technology, which is identified with applied science. This is when science comes into contact with society. Until then, the scientific activity has been internal.

According to Latour, this model of diffusion of science (37) is inadequate and the supposed border between the inside and the outside of science is fictitious: “all our examples have sketched a constant mixture, on both sides, between the outside world and the laboratory “38. Latour is right to criticize this model, and in particular to deny the identification between technology and applied science. Some philosophers of technology have also insisted that this identification is erroneous, 39 since historical examples abound in which technology has its own paradigms and technological trajectories, to use the names proposed by Nelson, Winter and Dosi 40. By our In part, we consider that science and technology have been autonomous from each other until the emergence and consolidation of technoscience, notwithstanding the fact that they have established very close ties throughout the industrial revolution.

The drawback of Latour’s thesis is that, determined to deny the identification between technology and applied science, as well as internal / external distinction, ends up confusing science, technology and technoscience. Reading his Science in Action, it would seem that all science has become technoscience, a thesis to which we strictly oppose. Neither the deployment of the Great Science prevented During the twentieth century, Small Science continued to be the nor the irruption of technoscience has devoured science and technology. Craft technique, science and technology continue to exist. What it is about is to analyze the new modality of scientific-technological activity, not to think that everything is technoscience. Such is, in our opinion, the main drawback of Latour’s theses on technoscience: they wipe out the nuances and differences between techniques, sciences, technologies and technosciences.

On the other hand, the problem does not lie in internal / external opposition. This distinction can be methodologically useful in some moments, although, from our perspective, it is preferable to talk about open technoscientific systems that interact with society in very diverse fields: laboratories, R & D offices, scientific-technological policy directions, classrooms, specialized publications, dissemination magazines, scientific press, telematic networks, etc. In general, it is convenient to talk about scientific-technological networks more or less consolidated and imbricated in societies, but never isolated in ivory towers. Do not forget that these networks are transnational, so technoscience is not immersed as a subsystem in a particular society, but affects several societies at once, and differently in each of them, depending on their peculiarities cultural and social As we have already indicated elsewhere, 42 another of Latour’s main shortcomings and the sociologists of scientific knowledge is that they use a very ambiguous notion of “society.” Of little use to say that the social is present in laboratories (which is obvious) or that science, technology and society are closely linked if the notions of “science”, “technology” and “society” are not minimally clarified . Sociologists of scientific knowledge have talked a lot about science, and more recently some technology, but very little about society. Reading their writings, it would seem that the notion of society they use is clear and intuitive, which is far from happening.

Another author who systematically uses the term “technoscience” is Gilbert Hottois 43. To introduce the notion of technoscience, Hottois relies on various authors, who, whether or not they used this term, had pointed out in the 70s and 80s this progressive convergence between Science and technology. Consider the following quotes to summarize this generalized trend:

H. Stork: “This distinction (between science and technique), apparently clear, is questioned by the growing intertwining of the natural sciences and technology, which manifests itself both as a technification of science and as a scientification of science. the technique “44.

W. Barret: “The new science is, by its essence, technological” 45.

J.J. Salomon: “Just as science creates new technical beings, the technique creates new lines of scientific objects. The border is so tenuous that you can not distinguish between the attitude of the scientist’s spirit and that of the engineer, since there are intermediate cases “46.

F. Gros: “The interdependence between progress in basic biology and pharmacology is total: pharmacology depends on all acquisitions in biology, medications are and will be, increasingly, a fundamental element for basic research” 47.

J. Ladrière: “Due to its deep roots, contemporary technological activity is linked to scientific practice. On the other hand, this union is all the more evident the more it is associated with advanced forms of technology “…” It seems, then, that there is a specific character in contemporary technology: its close interaction with science. This raises, immediately, two questions. On the one hand, it leads us to ask ourselves, considering the intensity of this interaction, if there is still a true distinction between science and technology and, on the other hand, to explain how this interaction is possible. Apparently, the frontier between science and technology fades more and more “48.

We could mention many other authors who have underlined this convergence between science and technology, coming to question the existence of borders between both. The more speculative and ontological these philosophers are, the more they tend to identify science and technology, regardless of differences. The reductionist mood is very common and in this case it is manifested taking the part by the whole. The growing link between scientific and technological activities is very true. But we must not forget that there are still scientific and technological areas where this process does not occur. Not everything is technoscience. There are important differences between science, technology and technology. The greatest conceptual risk consists of making the term “technoscience” omnicomprehensive, a defect in which many authors incur. Some place technoscience in Newton’s time 49, incurring a clear anachronism, that is, projecting the current models of technoscience onto the past.

Throughout this chapter we intend to clarify and clarify the concept of technoscience, distinguishing it from technology, science and technology. We will do it step by step, since this notion covers very different aspects, and if you want heterogeneous.

I.6: Methodological details.

It is important that, before proceeding, we make clear the conceptual framework in which the proposals and precisions that we are going to make are presented.

In the first place, we do not intend to define the notion of technoscience. We will limit ourselves to pointing out a series of distinctive features between science, technology and technoscience 50.

Second, those distinctions will be gradual, not demarcational. It is not about defining borders between science and technoscience, since the second is a particular type of science. Even so, the distinctive notes that we will propose will allow us to discern with sufficient clarity the one and the other, in most cases by the greater or lesser degree with which both satisfy said notes.

Third, we will not resort to the procedure of the specific difference, but to that of the distinguishing features or marks. 51. We are not interested in the difference between science and technoscience, but rather the open system of distinctive features between both. The differences are several, there is not one that is determinant of the others. In order to qualify an activity as technoscientific, many of these distinctive features must be satisfied to a greater or lesser degree, not just one. Once the concept of technoscience has been elucidated through this methodology, we will be faced with a clearer and more precise concept, without prejudice to the fact that the elucidation we are going to propose can be improved. In other words: in no way do we intend to investigate the “essence” of technoscience, for a simple reason. There is no such thing 52.

Fourth, our perspective is not reductionist. Although technoscience has emerged throughout the twentieth century, human beings continue and will continue to develop technical, technological and scientific activities. Therefore, throughout this book we will affirm that, in addition to technology, science and technology (plus art, which must also be taken into account in this debate), during the 20th century a new modality of human and social activity, technoscience, which has been consolidated sociologically and institutionally in the final decades of the previous century and only in some countries. Predictably, technoscience will have a great development during the 21st century. However, in no way do we think that this supposes the disappearance of science or technology. There is still art, science, technology and technology. In addition, there is technoscience. It is about analyzing this new activity, whose social importance is growing, without for that reason disregarding the others.

Fifth, the emergence of technoscience can be considered as a new type of revolution, which is not a scientific revolution in Kuhn’s sense or a technological revolution in the sense of Solla Price. Once the concept of technoscience is clarified, we will deal with the notion of a techno-scientific revolution.

Sixth, we will talk mainly about action and activity, more than scientific knowledge and technological artifacts. This is the main change we propose when studying the techno-scientific revolution. The philosophy of science of the twentieth century focused, with very few exceptions (Hacking, Rouse 53), on the analysis, reconstruction and, where appropriate, justification and justification of scientific knowledge. The sociology of scientific knowledge (Strong Program, EPOR, social constructivism, etc.) dealt almost exclusively with the social construction of scientific knowledge, although in the last decade of the 20th century there has been a praxiological turn (Pickering 54) and a certain interest in the sociology of technology, still very embryonic. Some historians of science (Franklin, Buchwald, Galison, etc. 55) have also become interested in recent years in scientific practice, especially in experimentation. As we have already stated elsewhere, the philosophy of technoscience must include first and foremost a philosophy of scientific and technological activity, 56 whose main reference will be techno-scientific actions, rather than scientific facts. In order to know the scientific facts, it is necessary to previously carry out diverse, typically scientific actions: observe, measure, calculate, experiment, conjecture, evaluate, demonstrate, etc. In the case of technoscience, all these actions are mediated by technology, to the extent that they can not be carried out or results can be obtained (observations, measurements, data, experiments, etc.) without having an instrument and without having various technical skills. There are no techno-scientific facts without techno-scientific actions and this is why we must begin with a philosophy of techno-scientific action. Technoscience is distinguished from science by that technological mediation inherent in techno-scientific actions. It is not enough with an epistemology and a methodology. Philosophy of science and studies of science and technology require a praxiology, that is, a theory of techno-scientific praxis. Techno-scientific revolutions arise due to a change in the structure of scientific and technological activity, which usually leads to a change in the structure of knowledge, but also many other transformations: political, economic, organizational, social, etc. This will be one of the basic theses of this book: technoscience has arisen by a profound change in the structure of scientific practice, not by an epistemological or methodological revolution.

Seventh, we will insist that, within that praxiology, we must develop an axiology of technoscience. The fifth chapter aims to lay its foundations, continuing the work done on the axiology of science 57. If we conceive science and technology as activities, then it is easier to compare them and to specify the differences between science, technology and technology. . That distinction can be established from many perspectives, but here we will focus on one: values. We start from the hypothesis that human actions are guided by values and by value systems. In addition, our approach to the axiology of technoscience will be systemic. Well, there are significant differences between the value systems that guide technical, scientific, technological and techno-scientific actions. Therefore, to distinguish between science and technoscience we will investigate the values underlying these two types of activity. Other authors will establish epistemological, sociological or other differences. On our part, we try to characterize the values of science to distinguish science from technoscience through axiological criteria.

A final methodological consideration, which will be further developed in section II.3. The philosophy of science deals with multiple sciences and for that reason it is usually distinguished between the philosophy of mathematics, physics, biology, social sciences, medicine, etc. When talking about technoscience, it will be necessary to explore the existence of different modalities of it: techno-mathematics, technophysics, technochemistry, technobiology, technomedicine, etc. The notion of technoscience will be concretized when we talk about its various modalities and analyze the various examples. Then it will be when the enormous changes brought about by the emergence of technoscience are perceived more clearly. The most classical scientific actions (demonstrate, observe, measure, experiment, etc.) have been radically modified by the effect of technoscience, and this has happened in almost all scientific disciplines throughout the 20th century, if not all. That is why we talk about technosciences, rather than technoscience.

I.7.- Characterization of technology and technology.

In his work Technology: a philosophical approach 58, Quintanilla tried to define entities as complex as technology and technology. Your proposal deserves a detailed consideration, although it seems improvable in some points. If we dedicate ourselves to the studies of science, technology and society (CTS) from a philosophical perspective, it is convenient to elucidate the concepts that we are going to use, as far as possible. The common use of words can make us believe that we know what science, technology or society are because we talk about them and we get to communicate and make ourselves understood. But the conceptual analysis allows to discover nuances and difficulties in the analyzed notions, that usually are hidden in the current use of those words. A thorough analysis of the multiple misunderstandings that result from speech acts would show that accuracy is a value in philosophy, which must be adequately met.

In this section we will comment on the definitions proposed by Quintanilla for the notions of “technique” and “technology”. Quintanilla recalls that: “specialized literature tends to reserve the term” technique “for pre-scientific artisan techniques, and technology for industrial techniques linked to scientific knowledge” 59. That is why it distinguishes artisanal or pre-industrial techniques and techniques. related to science, reserving the term “technology” for the latter. We will accept that distinction, although we have already indicated that many technological advances of the industrial age arose independently of science, interrelated with it later. To say that technologies are linked to science does not imply conceiving them as applied sciences. Given this precision, as an example, we will say that writing and printing are technical, the press, telegraph and photocopiers are technologies, and computers, electronic writing and hypertext are technosciences.

Then, Quintanilla introduces a second distinction between proper technique and realization or specific application of a technique: “techniques are abstract cultural entities, which may have different embodiments or applications and can be formulated or represented in different ways [.. .] and we could define them as the set of all possible technical realizations possible with that machine “60. Retaking the distinction of Amartya Sen between capabilities (capabilities) and realizations (or operations, functionnings), we would say that technology and technology induce new capacities of action, and in particular of repetition and reiteration of said actions 61. Each concrete case is a technical (or technological) realization. The notion of technique thus depends on how we define what a technical realization is:

Definition 1: “A technical realization is a system of human actions intentionally oriented to the transformation of concrete objects to efficiently achieve a valuable result” 62.

It is a very elaborate definition, which, in the case of technology, can be paraphrased in the following way:

Definition 2: “A technological realization (or application) is a system of human actions, industrial and linked to science, intentionally oriented to the transformation of concrete objects to efficiently achieve valuable results.”

Let’s distinguish each one of the notes that are included in this definition by assigning them letters, in order to be able to refer later to them:

(2a): system

(2b): of actions

(2c): human,

(2d): industrial

(2e): linked to science, (2f): intentionally oriented (2g): to transformation

(2h): of objects

(2i): concrete

(2j): to get

(2k): efficiently

(2l): results

(2m): valuable.

We will comment very briefly the notes 2a and 2b, in spite of being the most determining of the conception of Quintanilla. By virtue of 2a, his theory of technology is inserted within systems theory, as the author himself amply showed in the aforementioned book 63. This decision has multiple consequences, because it implies accepting that, rather than with isolated artifacts, we we have to do with technical systems, which we will call technosystems. These systems have an internal structure, that of their own subsystems, whose composition or assembly becomes indispensable for the subsequent realization of technical actions 64. The proper coupling between the various subsystems is the responsibility of the technicians, whose action is indispensable for the proper functioning of a technosystem. On the other hand, a system always interacts with a medium or external environment. The initial and contour conditions influence the operation of technological systems. Technologies are influenced by the societies that generate and drive them, for example the industrial society. Under certain conditions the systems may have emergent (or supervening) properties, as well as reach (or not) homeostatic equilibria. The choice of systems theory as a general framework for the philosophy of technology has many consequences, some of which we have just mentioned. In the next section we will see that this systemic conception is useful when looking for distinctive features for technoscience.

Under 2b, the philosophy of technology should not focus on artifacts or machines, but on the actions that can be carried out thanks to them. This philosophical option also has very important consequences, because it links the philosophy of technology with the theory of action: with it Quintanilla moves away from all forms of instrumentalism and technological determinism, underlining that the agents of technical actions are people, not the machines. In our view, here lies one of the great contributions of this definition, although we will not go into that point further. In the case of technoscience we will use the theory of action that we have already shown elsewhere. 65 As Aracil has pointed out, in every technological action it is “assumed that the agent has adequate representation of both the object on which he acts and of the objectives that are intended with the action “66. Precisely for this reason the previous design of the actions is usual in technology, unlike human actions in general. The existence of these designs, prototypes, representations or simulations is of great philosophical importance, as many authors have underlined, 67 because technological actions arise from more or less approximate representations of what is to be achieved. This phase of pre-action (and also of pro-action, since these previous designs are pro-active) requires a very characteristic type of instruments: sketches, diagrams, plans, models, scale models, simulations, etc. Not all of them are possible or feasible, so in technology we have to talk about possible action spaces. It is also necessary to take care of the composition of these schemes, which is normally done by subsystems, to proceed later to their assembly or subsequent integration. An engineer, an inventor and a designer previously conceive what they want to do and represent it (mentally, in writing, materially, etc.) before carrying it out. Well, we will insist that the emergence of technoscience has been made possible by the appearance of a new instrument of representation, or better, by a new formalism: information technology. That is why we say that technoscience is linked to the information society 68, rather than to the industrial society (which also, as it is technology). In any case, note 2b has numerous philosophical consequences, as briefly indicated above.

Note 2c “excludes from the scope of the techniques the actions carried out systematically, but instinctively, by some animal species, as is the case with the construction of nests, burrows or beehives “69. This assertion can be debatable in the case of techniques, but not in the case of technologies: as these are industrial and based on scientific knowledge, it is clear that only human beings they can carry out technological actions, or at most some machines built by the human beings themselves. However, Quintanilla’s use of the term “human” has an unintended consequence, as pointed out by López Cerezo70: it is hidden what groups or what people are the agents of these technological actions, when they are attributed to human beings in general. Likewise, technological actions carried out by automata are dispensed with, even though said automata have been designed by human beings to carry them out. This is one of the reasons why in our characterization of technological actions we always include agents (actors, doers, etc.) as the first component of said actions. Being true that technological actions are human actions, it is necessary to specify more the agents that promote or carry them out. In particular, the objectives of the same action can be different according to the agents, as well as the valuations of said action. In the axiology of technoscience we will find ourselves continuously with conflicts of values, and also with opposing objectives. Therefore it is necessary to clarify note 2c of the definition of Quintanilla.

Regarding notes 2d and 2e, we will accept them initially, although in the next section we will introduce an important qualification in relation to 2e. Nor will we analyze note 2f, because this would imply addressing the complex issue of intentionality, which falls outside the framework of this work. Note 2g has great philosophical importance: technologies do not try to describe, explain or predict the world, unlike sciences, but tend to transform it, be it the microcosms, mesocosms or macrocosms. This is one of the reasons why the philosophy of technology differs from epistemology and philosophy of science, and therefore we fully accept the note 2g. On the other hand, with regard to note 2h, we can make qualifications, as we have already explained elsewhere 71, as well as note 2i: techniques not only transform concrete objects (materials), but also abstract objects, for example mathematical objects . Algorithms, equation solving methods and scientific visualization techniques are good examples of technical actions that transform non-material objects, or if you prefer intangibles. There are also techniques that modify the habits of action and behavior. Sáez Vacas has called information and communication technologies (ICT) nootechnologies 72 because they transform information and knowledge, not just material objects. It is necessary to extend note 2h if we want to apply that definition to ICTs, which are one of the canonical examples of contemporary technoscience. On the other hand, these examples serve to show that technologies not only transform objects, but also relationships, actions, habits, etc. Therefore, we will say that technical and technological actions, being systemic, in turn transform systems, be they natural, social, economic or conceptual, or in turn small or large. In particular, one technological system can profoundly transform another, something that will happen everywhere in the case of technoscience.

Note 2j alludes to the objectives of technological actions, which must be distinguished from the intentions of their agents. The artifacts are usually designed to fulfill such and such objectives or functions, although later those who use them can Do it with very different intentions. This is one of the reasons why it is convenient to distinguish between the intentions of the agents and the objectives of technological actions. Regarding the note 2k, it can be eliminated, because not all technological actions try to maximize efficiency, contrary to what Quintanilla thinks, for whom the role of said value in technology is comparable to the value “truth” in the case of the science. As you will see in Chapter 4, efficiency is an important technological value, but not the only one, and sometimes not even the main one. For this reason, we prefer to eliminate the 2k note of the definition of technology, since it is redundant with the note 2m. If technological actions are efficient, they will be highly valued in relation to said value. But there are also highly inefficient technological actions, which do not stop being technological: for example, errors. On the other hand, we fully accept the importance of the notion of “results”, since if something is appreciated the technology is for its results. However, we should not limit ourselves to considering the immediate results of technological actions, but also their consequences and risks derived. Therefore, we will break down the concept “results”, including the consequences and risks that result from these actions.

Despite all the above, our main objective is to analyze the last note of the definition, 2m (valuable), for being central to the axiology of technoscience, without prejudice to the interest of the remaining points for our inquiry. From our perspective, it does not matter that the results are valuable. The agents, the actions, the objects on which they are carried out are also evaluated and, although not only they, also the intentions. Above all, the consequences and risks that could arise from the achievement of techno-scientific results must be evaluated. The moral dilemma that the atomic bomb posed for many nuclear physicists perfectly illustrates this requirement of not only assessing the expected results, but also the unforeseen consequences. To paraphrase Popper, you have to be a falsificationist in technology philosophy. Once we have assessed the favorable results, we must move on to consider the possible unfavorable consequences, including the risks that arise from possible errors in technological actions. The axiology not only includes values, also disvalores or counter-values. In summary, note 2m will acquire greater extension and relevance than in the Quintanilla proposal.

Carried by his interest in opposing his proposal to the artifactual conception of technology, Quintanilla did not include in his definition the instruments that allow to carry out technical and technological actions. We fully agree with his criticism of the identification of technology with machines, but this does not prevent to recognize that they also have a role in technological actions. Therefore, we will add a new note that reflects that instrumental component that always have the actions, both technical and technological. As we will see later, this will involve broadening the notion of an instrument. A mathematical notation and a computer program can also be technical instruments, so that our notion of an instrument will be wider than that of a machine. For example, we include technologies of social transformation (for example advertising) in our notion of technology. Surveys, statistical analyzes, etc., are also technical, and in many cases, technologies. In the case of computer science, which will have an important role when it comes to characterizing the notion of technoscience, it is necessary to take into account that info-actions are carried out by means of specific instruments, for example when making behavioral simulations. of the systems. The same applies to experimental actions, which are so relevant in macro-science. To forget the importance of the instruments of observation, measurement, experimentation and simulation in current scientific practice would be a clear conceptual insufficiency. For the axiology of technoscience, this is essential, because decisions are often made based on the instruments necessary to carry out techno-scientific actions, for example the assessment of their economic cost.

On the other hand, technological actions are usually regulated, particularly the use of instruments. We think of the instructions for use of any device, 73 but also of the legal norms that are frequently promulgated in this regard, for example, the highway code when driving a car. As a consequence of this we will add one more note, which refers to the rules that govern technological actions, some of which are norms or laws, but not all. Some of these rules are internalized by users after the learning process, so they become part of their tacit knowledge. However, this does not imply that they cease to exist as technical doing regulations. The domain of the rules of use is an important component in the theory of technical action. As we have already pointed out, technological actions can be inefficient, for example when an error is made for not having followed the rules of use of a device or the protocols for action. When systems are complex, as in the case of technoscience, it is necessary to explicitly specify the rules of action, for example to prevent risks. Therefore, it seems necessary to add this distinctive feature when characterizing the notion of technology, and much more that of technoscience.

Following this comment to the definition proposed by Quintanilla, we can provisionally accept the:

Definition 3: “A technological realization (or application) is a system of regulated actions, industrial and linked to science, carried out by agents, with the help of instruments, and intentionally oriented to the transformation of other systems in order to achieve valuable results avoiding unfavorable consequences and risks “74.

Once this definition is formulated, some qualifications must be made. In the first place, the difference between technique and technology will often be a distinction of degrees. The two distinguishing marks that we have accepted (scientific knowledge and industry) do not work as criteria for demarcation or separation. In the end, the boundaries between technology, technology and technology are not rigid or insurmountable, but gradual and permeable. This does not prevent, however, so that we can discern the three. The same is true of the distinction between science and technoscience, as we will see in the next section.

For this reason, we are not faced with an authentic definition, much less with a definition by gender and specific difference, but rather with a characterization of technology and technology. Nor do we rule out that more distinctive features of technology can be added. Broncano, for example, has insisted on the importance of technological design: “designs are the language that allows creating and producing technical objects” … “they are the very form in which technical objects are produced” 75. We ourselves We have previously suggested some additional features, derived from technological pre-actions and representations that allow us to imagine, project and design them, before carrying them out. From an axiological perspective, it is important to emphasize that these previous designs are always valued, first by the designer himself, then by the artisans or technicians who have to convert the design into an artifact. Therefore, the evaluation processes are prior to the technical actions, or if you want, concomitant to them. It should also be noted that technical designs usually take the form of diagrams, diagrams, etc. Unlike scientific knowledge, which is usually expressed through statements, laws or mathematical formulas, the design of technical artifacts is done through specific images and symbols. The technological representations are not linguistic, but ideographic. Hence the importance of computer science for the emergence of technoscience: computers not only represent statements, laws and formulas, but also images, diagrams and diagrams. The synthesis of scientific and technological knowledge occurs primarily through computer languages, which not only use bits, but also pixels. Therefore we affirm that informatics is the formalism of technoscience.

The characterization of the technological actions that we have just done is open: we can add new distinctive features to those considered in the definition 3. In any case, for our investigation it is important to have it. We will see that technoscience is characterized because scientific actions become technological actions, being included in a system of science and technology that constitutes one of the main social technologies of our time.

Chapter II Characterization of Technoscience

II.1: Distinctive features between science and technoscience.

Throughout history many definitions of science have been proposed 76. The same can be said in the case of technology, although the definition of Quintanilla that we have discussed in the previous chapter is one of the most elaborate. That’s why we take it as a starting point. It is now a question of specifying the features that distinguish technoscience from science and technology, based on the considerations already made in section I.4, regarding macro-science. There are differences in size and scale, but we will also propose qualitative distinctions. As a whole, the distinctive notes that we are going to propose configure a new framework for scientific-technological activity, very different from that of modern science or that of industrial technology. In this lies the uniqueness of technoscience, towards whose discernment this second conceptual approach is directed. The important thing is to have criteria to distinguish technoscience, science and technology, without implying a demarcation between them, since their respective borders are diffuse in some aspects. Since technoscience has a strong technological component, what was said in the previous chapter on technology is applicable to technoscience. It is now about adding other distinctive notes.

Technoscience can be considered as an evolutionary phase after the emergence of Big Science, after the crisis of the decade 1966-76. As we already said in the prologue, the continued growth of the macro-science in the US experienced a break from 1965, a date that marks the first crisis of macro-science, and in particular of the militarized macro-science. By then, this new form of scientific research had been consolidated in the US, the USSR, and was beginning to be established in some European countries (CERN, European Spacial Agency, etc.). The promotion of macro science in Europe and the USSR was also a governmental initiative, to a greater extent even than in the US. There were important differences between the science and technology system of the USA and, for example, that of the USSR, but the six characteristics of the macroscience that we pointed out in section I.4 are valid for Europe and the USSR, with the important difference that, in the latter case, the industries were exclusively state-owned and controlled by a political party. In the absence of rigorous studies on the structure of the science and technology system in the USSR, we will maintain the hypothesis that there was macro-science in the Soviet bloc, but technoscience was not taken, precisely because it lacked a business system and a market economy that would allow opening new sources of funding for techno-scientific research, apart from state ones.

Therefore, the six distinctive features continue to be valid, although with important nuances and differences, which should be underlined. But there are also new features.

In section II.2 we will put the accent on the latter. In the exploration carried out in section I.4 we had found differential notes of very different types: economic, sociological, political, etc. The indicators that many authors use to define macroscience have undoubted interest: size, rate of growth, economic percentage of investments in macroprojects, etc. However, our analysis starts from a philosophical perspective and focuses on axiology. As we expose these distinctive features we will make a brief axiological analysis of them, in order to show the deep changes of values that science has experienced in the 20th century. In chapter 5 we will deal exclusively with the axiology of technoscience.

(a): Private financing of research.

The macro-science emerged in the United States of America at the time of the Second World War and the main factor that prompted its emergence was a new policy of the Federal Government, more interventionist in scientific matters. The governmental initiative, in particular the military one, was the driving force behind the great projects of the 1940s and 1950s, notwithstanding the fact that in the 1930s some institutions would have been pioneers of American macro-science. From the point of view of financing, this policy remained stable until the middle of the 1960s, reaching its peak with the Kennedy 77 administration. From that moment, and coinciding with the failure of the Vietnam War, It produced a profound movement of distrust of science on the part of American society, which was directly reflected in the public budgets that were dedicated to it and in numerous student and social movements against the military applications of scientific research. 78. The military financing of the Basic research, for example, fell sharply in the period 1965-1975 79. The same happened with private financing, which fell by 36% between 1966 and 1972.

The scientific communities experienced this fall as an authentic crisis and even spoke of an irrationalist and anti-scientific movement 80. Many universities closed their research centers linked to Defense, or reconverted them. The situation began to change with the Ford Presidency, but especially with the Reagan Administration. In the 1980s, a new social contract with science was established, which can be considered as the basis for the emergence of technoscience. From the budgetary point of view, there was a rapid growth of private financing in R & D, thanks to a liberalization of the patent law and a new fiscal policy, which allowed to deduct 25% of private investments in R & D . The political priority became technological development and the presence of the private initiative as the driving force behind it. The Government did not stop financing basic research, but the main objective of its scientific policy was to make it possible for companies to increase this funding. This policy brought about a radical change in the framework in which scientific research was developed. Since the 1980s, private R & D funding has exceeded public funding, and since then it has continued to grow, reaching 70% of total R & D investment in the US. A similar process occurred in Europe, although much later. 

Therefore, we will say that technoscience proper emerges in the 80s in the US, without prejudice to previous precedents of it. From the point of view of financing, it is characterized by the primacy of the private sector over the public. This change brought with it many other concomitant transformations, which should be analyzed separately. In general terms, it represented an important restructuring of the North American system of science and technology.

For example, the Stock Exchange became interested in investing in science and technology. In 1983, companies such as Merrill Lynch and Banca Morgan advised their clients to invest in R & D companies. Facing the financing of the macro-science, mostly state and military, technoscience found new ways of financing, apart from large corporations and government agencies. Small R & D companies proliferated, especially in the field of new technologies (ICT, biotechnologies). Many of them turned to venture capital financial entities and to the Stock Exchange to launch their research programs, which were not focused only on basic research and technological development, but above all on innovation. Since the 1980s, the size of the R & D companies, which had become R & D & I, was no longer the key. The important thing was its ability to innovate and penetrate the market of new technologies. A few years later, all this came together in the appearance of a new stock index, the NASDAQ, where techno-scientific companies found a new source of financing and market capitalization. Most of these small R & D & I companies perished or were absorbed by large corporations, but some of them survived and became large companies in the techno-scientific economic sector. There continued to be scientific macro-projects financed by the Government, so that macro-science continued to exist. But, apart from it, a new form of science emerged, whose research had as a priority the technological innovation. The size of projects, equipment and instruments was not relevant in the case of techno-scientific companies. It is one of the reasons why we distinguish between macroscience and technoscience. Some small companies (Apple, Microsoft, Intel, etc.) showed much greater innovative capacity than the large industrial corporations of the postwar period. Their growth rates were very high, although many of them were ephemeral. Technoscience became a sector where you could do good and fast business if technological innovations were achieved. Therefore, the stock market and private investors were attracted by the new sector, leaving the macroprojects for state agencies. Together, this new scientific-financial policy got the percentages of public and private research funding reversed. The primacy of private investment has since become a structural component of the North American SCyT systems, which many other countries try to imitate. Macro-science and technoscience are clearly distinguished by their financial structure.

From an axiological perspective, it can be said that with the arrival of technoscience the most characteristic values of capitalism entered the very core of scientific-technological activity. Rapid enrichment, for example, which had traditionally been alien to scientific communities, became part of the objectives of techno-scientific companies. Stock market capitalization and investor confidence became dominant values for many techno-scientific companies. Although the classical values of science maintained their presence at the time of research, the R & D & I companies did not aim to generate knowledge, but rather technological innovation and its capitalization in the market. The relative weight of technical, economic and business values increased considerably, while the political values of the time of the Second World War declined. On the other hand, many techno-scientific companies became multinationals, overflowing the North American market, so they began to be more sensitive to cultural, ecological and social values, whose adequate satisfaction was necessary to achieve greater penetration levels in international markets. Legal values also gained great weight, insofar as knowledge ownership, patent management and licenses for the use of technological devices had to be ensured.

(b): Mutual mediation between science and technology.

The relations between science and technology come from the industrial society and were considerably reinforced by the emergence of macro science. In the case of technoscience, the interdependence between science and technology is practically total. If technoscientists seek to produce new knowledge and undertake scientific actions for it (demonstrate, calculate, observe, measure, experiment, etc.), these actions are literally unviable without technological support. Reciprocally, technical skills and technological innovations must be strictly based on scientific knowledge, not only linked to it, because this increases the economic efficiency of technological actions. The design of the experiments and of the scientific research projects is technological, since it is necessary to enunciate previously some objectives, to specify a methodology and a work plan and to foresee the results that they intend to obtain, assessing their possible importance and usefulness, as well as the expectations of generating innovation. Reciprocally, the various technological actions must have a scientific basis. Science is a requirement of technology and science technology. This hybridization is a constituent part of technoscience, unlike industrial science and technology, where it was adventitious. With technoscience a mixture or fusion is produced, because both activities benefit one another. The greater or lesser degree of integration between scientific and technological activity is one of the indicators of the existence of technoscience, although, for practical purposes, it is sufficient to determine if each of them is indispensable for the other. The symbiosis between science and technology had already taken place at the time of the macroscience, but from the 1980s it was reinforced again, possibly with more prominence for the technologists.

This distinctive feature can be analyzed from multiple perspectives (institutional, sociological, economic …), but here we will deal primarily with its axiological interpretation. Being technology, technoscience not only seeks true (or credible, or testable, or falsifiable) knowledge, but also useful knowledge 81. But, being a science, it is not enough for techno-scientific actions to be useful or effective, but also it requires that they be scientifically justified. Hence, technoscience, despite having a very strong practical orientation, is always interested in theory, including the theory of artifacts applied 82. Truth, verisimilitude, generality, empirical adequacy, precision and coherence they are still relevant values for technoscience, but epistemic values are not the only ones. Technoscience incorporates a good part of its technical values (utility, efficiency, effectiveness, functionality, applicability, etc.) into its axiological core and, although it still maintains epistemic values, the second subsystem of values has a weight as great as the first. Technoscience and science are distinguished from each other by the greater or lesser relative weight of these two subsystems of values, notwithstanding that both incorporate epistemic and technical values to their axiological core. This first distinction is a matter of degree, but also of preponderant value systems. In science, epistemics predominate, technicians in technoscience.

(c): Techno-scientific companies.

The link between science, technology and business was intensified radically with the emergence of technoscience, to the point that the production of scientific and technological knowledge becomes a new economic sector, popularly called new technologies. Not only can we talk about techno-scientific industries, as happened in the case of macro-science, but a new market sector in which different types of companies compete (public and private, industrial and information, large or small). At the same time, laboratories and research teams struggle with each other to obtain public projects and contracts with companies, seeking niches in the financial market of technoscience. The obtaining, management and profitability of the patents resulting from research in R + D + i becomes a basic component of the techno-scientific activity, as important as the research itself. In addition, new forms of exploitation and profitability of the ownership of knowledge arise: user licenses, franchises, access and connection subscriptions, etc. Good part of the patrimony of these companies consists of the knowledge that they have in property, or that they are capable of producing, managing and commercializing. It begins to speak of intellectual capital, with what is implied that the investments in this type of capital must be profitable. On the other hand, it is no longer enough to produce knowledge, but it is necessary to know, both when proposing research projects that are promising and when presenting the results. The management and marketing of knowledge is part of the activities of a techno-scientific company. Whether it is public, private or mixed companies, business models of work organization and technoscience management are introduced, unlike classical academic communities, which are anchored in a way of producing knowledge that is outdated. As can be seen, the change is radical.

Additional consequence: techno-scientific results become merchandise and, instead of communicating freely and publicly in specialized journals, they become private property from the early stages of research. The greater weighting of economic values in the axiological core of scientific activity generates a systemic change in the values of technoscience. In the emergence phase of macro-science, this led to many conflicts, since “instead of exploring new phenomena, physicists found themselves spending more and more time investigating ways to achieve patentable ideas, for economic reasons, more that scientific “83. In contrast, from the 1980s these values are internalized by the scientists and engineers themselves, some of whom become shareholders of the companies where they work. R + D + i companies may be interested in scientific discoveries and that these are publishable at the time, because this is in favor of the prestige of the company; but much more interested in the development of research projects arise patents and leasing contracts, so that the knowledge is economically profitable. The arrival of private investment in technoscience brought with it the imperative of profitability of the knowledge. In most cases, “patentability” takes precedence over “publishability”, reversing one of the classic values of modern science. The potential achievement of patents is an evaluation criterion in the design of technoscientific projects, as well as their capacity for innovation, that is, the transfer of results to companies that act in the market. Technoscience not only assesses the epistemic impacts (publications, citations, etc.), but above all the economic impact of the resulting innovations, as well as the ability to obtain financing for the development of the projects. The techno-scientific culture has a strong business component, something that did not happen with modern science, with some exceptions.

We verify again that there is a profound change of values between technoscience and science. The technological communities had internalized to a greater degree the principles and business values during the industrial era. In the stage of macro science, scientists collaborated in large military projects for epistemic reasons (solving scientific problems), but also for political reasons (patriotism, defense of democracy, etc.). Now, on the other hand, the scientists themselves have taken on board the business values, without losing their specific epistemic values. Also in this case there are considerable differences of degree, since some techno-scientific companies tend to become large holdings, which are listed on the stock exchange or are integrated into financial groups. The marketing of technoscience becomes a common practice, whose design corresponds to experts in marketing, but scientists and engineers also emerge that stand out for their ability to “sell” or disseminate the product, rather than for their skills in the laboratory or with appliances. This process occurs first of all in the private sector, but also in science with public funding. The increasingly close links between universities and companies are a good indicator of it.

In summary, economic and business values permeate the techno-scientific activity and are integrated into the axiological core of research, teaching and the application of technoscience, acquiring a considerable relative weight. It is important to underline this fact, because it follows that the axiology of technoscience must always take into account, at least, three systems of values: epistemic, technical and economic. The current terminology to talk about them is: research, development and innovation, alluding in the latter case to the business components of the techno-scientific activity. Technoscience is always guided by economic values, which only happened occasionally in the case of science. Economic values are one of the three axiological components that guide technoscientific actions and their ex ante and ex post evaluations. Therefore, axiological pluralism is “connatural” to technoscience. Some classical sciences could be guided by exclusively epistemic, or predominantly epistemic, values. This does not happen in the case of technoscience and therefore we have a new axiological criterion to distinguish them: the existence of a subsystem of economic values together with the subsystems of epistemic and technical values mentioned above.

(d): Research networks.

If we look at the main scenario of modern science, the laboratory, technoscience brings significant changes. We saw that, in the case of macroscience, laboratories became factories of knowledge production. With the subsequent leap to technoscience, they take the form of network laboratories, interconnected thanks to information technologies. In front of the isolated laboratory of modern science, coordinated laboratories emerge, collaborating in the same project and dividing the tasks to be carried out. The same happens with research projects, in which different research teams, companies and countries usually collaborate. On the whole, the institutional atomism that characterized modern science has been replaced by a techno-science network, with all the consequences that this has for the organization of scientific activity and for research practice.

The Arpanet network, which connected several American universities and agencies in the 80s, can be considered as a first paradigm of network research, as well as the World Wide Web, designed by Berners-Lee to facilitate communication among researchers of the network. European CERN. To the laboratory formed by the physical enclosure where the investigators, the apparatuses and the objects investigated coincided, a laboratory-network was superimposed on him. The new space and military research programs of the USA, completely mediated by telematic networks, are two other great examples of this deep topological transformation of the main scenario where modern science, the laboratory, was developed. The remote access to large computers and equipment, the exchange of data, drafts and hypotheses through telematic networks and network research became from the 1980s a common scientific practice, notwithstanding that observations and experiments continue to develop. The objects investigated were computer representations, the empirical data became technodata and the research and testing teams were geographically dispersed, but connected by technology 84.

The name of technoscience is justified on the basis of this transformation of laboratories in network laboratories. Indeed, the most elementary scientific actions (obtaining and consulting data, performing calculations, testing hypotheses, exchanging ideas and provisional results, etc.) began to be mediated by the new information and communication technologies (ICT). . The scientists no longer kept the data in their desks or in the viewfinders of their instruments. To access empirical data and to obtain new data, the use of ICT is essential. Technoscience is characterized by the need to resort to ICT to develop the most routine scientific actions. The laboratory becomes a tele-laboratory.

The same applies to scientific publications, which have adopted an electronic format. The public communication of the results of the investigations began to take place in a technological scenario: at a distance and in a network. The verification and verification of data, observations, measurements, experiments and hypotheses, which was previously done through congresses, personal visits and prepublications, is now carried out on the Internet. Informal relationships among scientists, so important in consolidating the dominant currents in scientific communities, are developed through e-mail. A historian of twentieth century technoscience has to resort to documentary sources very different from the traditional protocols of laboratory to track the processes that lead to a discovery or techno-scientific innovation.

From an axiological point of view, this implies a reinforcement of technological values at the very core of scientific activity: the laboratory, the communication between scientists and the publication. The proper functioning of telematic networks is essential for network laboratories. It requires speed, reliability, robustness, compatibility, integrability, efficiency, good performance, etc. Not in vain has Internet2 emerged in the US when the use of the Internet has become widespread in civil society, creating operational problems in the telematic networks used by scientists. The generation, testing and improvement of scientific knowledge depends strictly on the proper functioning of telecommunications technologies, and this not only in relation to laboratory devices, but also to the other devices that allow access to data, its representation, its transmission and communication and scientific publication. A laboratory that is not connected to broadband networks is simply not a techno-scientific laboratory.

(e): Military technoscience.

From the first world war, and especially the second, scientists have been involved in military companies of a scale hitherto unknown in the history of mankind. The chemical war of 1915 was the first great example, 85 but the Manhattan project better illustrates what we have called militarized mega-science. The explosions of the atomic bombs of Hiroshima and Nagasaki gave rise to an authentic crisis of conscience in the scientific community, as well as in society. This crisis of values worsened further, because the development of nuclear energy generated enormous threats to the entire planet (greenhouse effect, waste, risks in nuclear power plants, etc.). In the following decades, there emerged forms of authentic militarized mega-science, such as the SAGE military network, put into operation by the US in the 1950s. Its main core was a computer network that controlled numerous radar devices, organizing the response and directing the fighters in case of a nuclear attack from the Soviet Union. The SAGE network inaugurated the saga of military techno-scientific networks, whose maximum exponent was President Reagan’s Strategic Defense Initiative, decisive for the consolidation of technoscience. This line of research led to a new form of warfare, the cyberwar, which has been implemented on a large scale in the Persian Gulf Wars, Kosovo and Afghanistan. As we have stated elsewhere, cyberwar implies a radical transformation of the concept of war 86, although here we will not expand on it.

Since the 1980s, collaboration between scientists and the military has once again been considered a priority in the US, and the crisis of the decade 1966-76 has been overcome. After the Vietnam War, the Pentagon began to claim that the US was losing its technological supremacy in relation to the USSR and that it was necessary to resume collaboration between scientists, engineers and the military, which had diminished considerably. Therefore, the new objective was to develop military technology, particularly in the field of ICT, remote-controlled missiles, microelectronics, lasers, artificial intelligence, robotics, new materials and new propulsion systems for weapons and ships. 87. As a result, the Ford and Carter administrations began to approve new funds to enhance basic research applied to defense issues. But also in this case it was the Reagan administration that took the most decisive measures: in 1986, the funds that the Universities could receive from military agencies increased by 16.5%. The novelty was that they were no longer research macroprojects. Although they continued to be used, a good part of the funds were used to finance small projects, provided that these offered expectations of innovation in military technologies. The private sector, for its part, also supported this initiative, investing in universities that had contracts with military agencies. The electronics sector, for example, grew 200% in fifteen years. Thus, the techno-war era, based on ICT, was inaugurated, unlike the war supported by heavy industries. Therefore, since the 1980s and in relation to militarized technoscience, it can be stated that:

e.1): The techno-scientific research, whether large or small, acquired a strategic relevance for the military powers. As a result of the priority accorded to military technologies, today we can speak of a new form of warfare, the infoguerra or cyberwar, based on technosciences, rather than the industrialized science of the early twentieth century. Latour goes on to state that “technoscience is part of a war machine, and must be studied as such” 88. This may be true in the case of some technosciences, not all of them. Above all, it is false when the term “technoscience” is used omnicomprensively, as Latour does, who assumes that science, technology and technoscience are the same, contrary to what we advocate here. On the other hand, Latour is right in stating that “today, no army is capable of winning without scientists” 89. Much of technoscience has great strategic importance for the military powers and for this reason innumerable technoscientific projects can be mentioned. that have been promoted, financed and developed by the armed forces of the USA. In other words, in addition to the links between scientists, technologists and entrepreneurs, technoscience is based on the establishment of very close relations with military power. This already happened in the megaciencia stage, but it was reinforced from the 80s decade. The Departments of Defense of the advanced countries have created their own Centers of scientific-technological research, whose innovations are essential for the development of new defense and attack weapons, as well as military telecommunications. Military technosciences are part of the basic structure of current military activity, including the work of information and propaganda, which is carried out through television and media.

e.2): One can speak, therefore, of a partial militarization of technoscience, which has multiple consequences in scientific activity, as well as in its results. Part of scientific knowledge and technological innovations become confidential and secret, breaking one of the basic values of modern science: the publicity of knowledge. They are not even registered in the patent registers. This does not imply that everything becomes secret. Public science and technology continue to exist. What happens is that, together with them, techno-scientific knowledge and innovations arise that are only transferred to civil society when they have been dismissed as confidential, because they have been overtaken by other innovations or by becoming obsolete. There are also many techno-scientific projects that never cease to be secret, because the documents related to them are destroyed. Using a military metaphor, we will say that the vanguard of technoscience is usually military, only the knowledge of the rear being made public. Civil society knows very little about what happens in the techno-scientific vanguard. Some projects never become known, because military values imply a will not to know everything that is planned or done, contrary to the scientific ethos that Merton talked about 90.

e.3): The sociological consequences of the above are considerable, since a considerable part of the technoscientists are at the service of the armies, directly or indirectly 91. This entails new changes in the technoscientific activity, to the extent that the discussion Free and critical of the hypotheses and of the options taken is radically juggled. Defending Popper’s critical rationalism in the context of militarized technoscience seems purely and simply an epistemological sarcasm.

e.4): Although we will not insist much on it, it is important to emphasize that knowledge and techno-scientific skills are not only creative, but also destructive. Destructive technoscience is an indispensable part of the new scientific activity, so it is difficult to continue affirming that knowledge is a good in itself, as many scientists usually say. It can be argued that destructive devices are constructed to defend themselves, or to dissuade, as Popper himself affirmed in relation to atomic bombs 92. But even if we accept that argument, we can conclude that the search for scientific knowledge becomes an instrument for other purposes, not an end in itself. The aims of technoscience are not those of science. As we have stated more than once, this subordination of the search for knowledge to other objectives (military, business, etc.) is one of the main differences between technoscience and science, at least as it has been theorized by the philosophers who conceive scientific rationality in terms of the objectives of science. If that theory of rationality is maintained, techno-scientific rationality differs radically from scientific rationality, since the objectives of technoscience have changed. The alternative is to advocate value or axiological rationality, as we will see in chapter 5.

These changes, and others that could be mentioned in relation to the links between technosciences and military power, including secret services, have a clear axiological transcript. In times of war there are profound changes in the values that guide scientific activity, without prejudice to the fact that there are scientists (the minority) who depart from that mainstream and try to maintain the purely epistemic values of science. Some of the military values (discipline, due obedience, patriotism or secrecy) enter the axiological core that guides scientific actions, not without conflicts or controversies, which are usually silenced. This is one of the reasons to affirm that the structure of scientific and technological activity changes radically in virtue of that close connection between technoscience and war. If we said before that the value system of technoscience has, at least, three subsystems (epistemic, technical and economic), we can now add a fourth subsystem, that of military values, since these are firmly embedded in scientific practice. We can conclude that a large part of the techno-scientific actions are guided in part by military values, and this is at the very core of them, that is, in the institutions and research companies, insofar as they are part of the military apparatus, although they are not are accounted for in the Armed Forces.

(f): The new social contract of technoscience.

Although in this case too many historical precedents could be pointed out, it can be affirmed that the notion of a scientific policy for times of peace arose in the USA during the Second World War. Since then it has been developed and disseminated by the most developed countries. A new type of techno-scientific action appeared: the design, discussion, approval, publication and putting into operation of Science and Technology Plans, with the subsequent creation of specific Agencies for it. Said plans are proposed by the Governments, and in their case debated and approved by the Parliaments. It is about political actions in the full sense of the word. Normally they are considered matters of State, around which a broad consensus among diverse social and political agents is sought. Through these actions the world is also transformed, but not the natural world, but a sector of the social system, namely: the SCyT scientific-technological systems of each country. The policy of science and technology (PCyT, for short) promotes, develops and transforms the context in which scientists will investigate and technologists to innovate. This context will be decisive in deciding which investigations are pertinent (or priority) and which are not. The actions for the provision of infrastructures and large equipment provide some equipment and research centers with the necessary equipment to carry out their activities. Calls for research grants and jobs for specific projects in universities, research centers and R & D companies generate human resources, without which specific techno-scientific actions would not be possible either. Calls for research programs and projects, as well as specific actions and major cross-cutting actions, allow the execution of techno-scientific projects by providing financing equipment and resources (consumables, temporary hiring, new instruments, etc.). The evaluation agencies institute procedures and criteria for these resource allocations and also allow the monitoring and ex post evaluation of the results. There are many other actions of scientific and technological policy apart from these four: for example the creation of new techno-scientific agents (research institutes, universities, technology parks, networks of excellence, etc.), or the definition of priority research lines and development, with the multiple consequences that result for the scientific communities. We do not intend here to deal in depth with the enormous complexity of the national systems of scientific-technological policy. For now, we merely point out that the establishment of these systems was a great novelty in the mid-twentieth century, which brought about a radical change in the scientific-technological activity, by creating new frameworks or contexts of action. Once again we are facing techno-scientific actions whose objectives are not to generate knowledge, but rather to create the conditions of possibility for research, development and innovation. The existence of technoscience depends entirely on these PCyT policies. In fact, technoscience has only emerged in countries where these types of policies exist, so that PCyTs have to be considered as a condition for the possibility of technoscience. Therefore, we are facing another of the distinctive features between science and technoscience. The first can exist and develop in the absence of previously designed scientific policies, the second does not. With more or less means, scientists have been able to drive research autonomously throughout history. Technoscience, on the other hand, requires an explicitly designed scientific-technological policy, be it public, private or secret.

The links between science and power predate technoscience, since they appeared at the end of the 19th century. The scientific communities have always sought to influence political areas, both to obtain funding for their activity and to show the social and political usefulness of their research (prestige of the country, modernization, solution of serious health, nutritional and industrial problems, etc.). This also applies to communities of engineers and technologists, who have become socially established as experts, advisors and professionals of great social prestige, in both political and business spheres. Thus, what Ron Ron has called the power of science was consolidated throughout the nineteenth and twentieth centuries. The American lobbies of scientists, military, technologists and large companies are the typical expression of this new power 94. After the Second World War, the changes were qualitative, because some scientists, starting with Vannevar Bush, were integrated into the very nucleus of political power. That is when what came to be known as scientific-technological policy with precision arises, as we will see in greater detail in chapter 4.

We have proven that the emergence of macro-science, its crisis, and the subsequent appearance of technoscience in the 1980s, were linked to important changes in US scientific policies. To defend their interests, many leading scientists have joined the agencies and committees that made the decisions, as well as directly advising the President of the United States. The period of the macro-science crisis coincides with the elimination by Nixon of the President’s scientific advisory council in January 1973 (Office of Sciece Policy), whose functions were transferred to the National Science Foundation. The rupture of the direct connection between the scientific communities and the Presidency was strongly criticized by the scientists, who spoke of a political counterrevolution against science 95. In April 1974, a Committee of the National Academy of Sciences recommended a “scientific presence and Technology in the White House “96. It is the time when the creation of agencies for the evaluation of technologies (Office of Technology Assessment) is proposed. Nelson Rockefeller, the Vice President of Ford, reversed that trend by creating an Office of Science and Technology Policy in the Executive Office of the Presidency. This allowed scientists to regain positions in the White House, although with much less influence than in the 40s and 50s. The restoration of political power by scientists continued with the Carter Administration, although some prestigious economists, such as Milton Friedman, they opposed that the Government and the White House returned to be involved in that type of questions. With the arrival of Reagan, the techno-scientific lobbies once again had great influence, contributing to the design of the policy of liberalization of patents and tax reduction for the aforementioned R & D companies. George Keyworth, Reagan’s scientific advisor, played a very important role in defining the new social contract of science, now focused on technological innovation. It must be said, therefore, that the changes in the scientific policy of the USA were decisive at the time of the crisis of the militarized macro-science and also in the emergence of technoscience.

From an axiological point of view, the change in values brought about by the insertion of scientists in the highest spheres of political power was enormous. The techno-scientific activity was imbued with political and legal values, since they are the ones that determine the framework in which the investigations will be developed and the way to present and carry them out, as well as the objectives. The priority lines are defined by governments and parliaments, as are the legal frameworks where techno-scientific actions can be deployed. Scientists and technologists who are inserted in the direction and redesign of the national systems of science and technology are obliged to assume legal, political and social values alien to their disciplines. For example, they must learn to propose balanced budgets, so that no scientific community or minimally powerful group feels damaged or excluded. This does not prevent them from strengthening some lines by increasing financing, through special actions or defining them as priority lines. An expert in scientific policy must master the budgetary and management arts, in addition to being very attentive to the systems of expenditure control imposed by the Parliaments and State auditors. Many apparently well-conceived scientific policy programs have failed because of poor management of them. Defining the National Science and Technology Plans, to use the terminology used in Spain, is one of the main techno-scientific actions, because the terms in which these plans are defined and the budgets assigned to each of the actions will be decisive when it comes to guiding techno-scientific development in one direction or another. Scientific and technological policy thus became a new discipline, which had to be mastered. The era of technoscience is characterized by the consolidation of scientific policy institutions and by the growing power of them. Those communities that do not have qualified representatives (and experts in the arts of politics) in these institutions usually have a black future. The traditional disdain of scientists by politicians disappears almost completely in the age of technoscience.

We confirm again the hypothesis of the axiological pluralism of techno-scientific activity and increase the number of subsystems of values that guide this activity. If not in the entire scientific community, at least some representatives of their corresponding elites have to fully internalize the procedures and values of political life. The political control of scientific research is one of the central topics of debate in the era of technoscience. In Reagan’s time, scientists managed to get these controls relaxed, recovering part of the management autonomy Vannevar Bush had achieved for them in the 1940s. Conflicts in this respect are continuous in the different systems of science and technology, for which also in this case we verify that the existence of conflicts of values are part of the core of the techno-scientific activity.

(g): Plurality of techno-scientific agents.

The transition from science to macro science changed the subject of science, transforming it into a plural subject. With the advent of technoscience, this change was consolidated and generalized. Today, it is assumed that a minimally important techno-scientific company, in addition to scientific researchers, engineers and technicians, must include other types of equipment: managers, advisors, experts in marketing and work organization, lawyers, allies in political fields. -military, financial support entities, etc. The techno-scientific agent has its own structure, because it is never formed by a single individual nor is it reduced to a group of scientists, engineers and technicians. Inside the techno-scientific companies, and as indispensable components of them, a great diversity of experts is included. All of them carry out essential tasks, although then it is the prestigious scientists who appear as spokespersons of said companies when it comes to publicizing their achievements, should they choose to make them public. Not only does the exterior of science change, as a new system of science and technology emerges. So important is the internal change. The interior of technoscience differs radically from within science, if we want to maintain internal / external distinction.

The philosophy of science debated at length about the objective character of scientific knowledge or, to put it in terms of Popper, about epistemology without subject. After a learning process, any human being could accept and make scientific knowledge his own. The minds of the individual scientists, the “men of science”, were the great reservoirs of knowledge, apart from the magazines, libraries and printed materials that were communicated to the rest of the scientific community. In the case of technoscience, on the other hand, complex and heterogeneous teams of people are required, as well as different types of media and instruments. The subject of technoscience is plural, not individual. Or better, it is not even possible to speak of the subject, but of agent, actor or maker. This is always plural, because it requires the collaboration of various types of experts and numerous artifacts so that a techno-scientific action produces acceptable results. From the individual subject of modern science (the genius) is passed to the research team with a whole business, administrative, political and legal support structure. For the results of scientific research to be fully acceptable, epistemic contributions are not enough. In addition, scientific knowledge is required to generate technological development and innovation, so that this knowledge is transferred to companies and institutions. Therefore, the very notion of acceptability is modified. To be so, techno-scientific companies have to internalize this change, organizing themselves in a different way.

From an axiological perspective, this implies that the actions of the subject of technoscience are guided by a plural system of values, since the very subject of technoscience is plural. Said subject can be visualized in the following way: it includes, at least, a scientist, an engineer, an entrepreneur, a soldier and a politician, although it can be broader and more varied, giving entrance to a jurist, an evaluator, an expert in management and an investor, without forgetting the marketing and administrative experts. Each of these agents acts according to their own values. Since all of them together make up the “subject of technoscience”, conflicts of values take place within that subject, because they are a plural subject. These conflicts will reach more or less stable equilibrium points, or not. In any case, we can conclude that conflicts of values are part of the structure of techno-scientific activity, contemplated from the axiological perspective in which we have placed ourselves.

II.2: Additional differences between science and technoscience.

Up to now we have taken into account the distinctive features presented in our analysis of the concept of macroscience, verifying that the differences between macroscience and technoscience are significant. This will be even clearer if, leaving aside our point of departure, we go deeper into the characterization of technoscience. In this section we will expand the list of differential notes.

(h): Technoscience and environment.

Some consequences of the emergence of technoscience have not yet been mentioned. One of them is its tremendous impact on the environment, particularly notable in the case of some technosciences, not in all. It must be said that the environment, including the social environment, is the patient subject of techno-scientific actions. Nuclear energy, with atomic bombs, reactors and nuclear waste, is a great example, but not the only one. Regarding the ecological impact of some techno-scientific advances, we must mention plastics, transgenic foods, genetic engineering, atmospheric waste generated by obsolete artificial satellites and many other examples that we will discuss throughout this work. It is not enough to take into account the immediate results of the research in terms of scientific achievements and technological innovations. It is also necessary to consider the environmental consequences of these actions, as well as their possible risks.

Some large impacts on the biosphere have generated considerable opposition to techno-scientific activity, insofar as it has great polluting effects on the natural environment. This pollution does not arise with technoscience, because industrialization had already generated tremendous environmental damage, both by the exploitation of raw materials and by the waste generated by industrial production (air pollution, global warming, industrial waste, etc.). . However, some technosciences (new materials, transgenic foods, etc.) transform the environment in such a way that they have impacts on large areas of the planet or on the ecosystem as a whole. 97. The emergence and consolidation of environmental movements, many of which activists have a high degree of scientific education, is one of the consequences of the transformation of science into technoscience. Since the crisis of macro-science in the 60s, a new relevant agent for techno-scientific activity has emerged: the environmental movement, whose strength is growing in the most technologically advanced countries. This current adopts multiple forms and modes of organization, depending on the countries and the problems addressed. In general, these are non-governmental organizations (NGOs), a name that expresses a clear distancing from the political institutions that have promoted macro-science and technoscience.

We are particularly interested in those environmental movements that have adopted some aspects of technoscience when it comes to acting, for example Green Peace. From our point of view, this organization is a more techno-scientific agent, although it intervenes from outside the SCyT system. The scientific education of its members and leaders is very high. In addition, many of their actions are carefully designed, so that they have a considerable impact on the media, and more specifically on television. Greenpeace uses some of the new information and communication technologies (television, Internet, etc.) in order to increase the social and political impact of its actions. He is able to negotiate with businessmen and politicians and is admitted as a valid interlocutor. Located on the periphery of the SCyT system, its actions have a great impact on its core, largely because some scientists and technologists, together with a significant part of society, share their ideas and morally support their actions. Greenpeace has found its source of financing in society, which allows it to have a minimum technological means to act. Its actions are thought to be contemplated in a technological scenario, for which it incorporates notable design techniques. Being a critical movement of technoscience, it has incorporated scientific knowledge and technology into its practice. That is why we affirm that it is a more techno-scientific agent, even though it operates from the counterpower.

These types of organizations have proliferated in recent years, for example, in opposition to GM foods, and achieve increasing social support. In some European countries (the most notable case is Germany) they have been constituted as political parties and participate in democratic governments, which allows them to influence decision-making in scientific policy. They have also obtained the approval of various laws, regulations and regulations that, although they are often not complied with, constitute a starting point for subsequent legal actions. In the 1990s, environmental issues have begun to be on the agendas of political power: Vice President Al Gore affirmed that “we must make the salvation of the environment the central organizing principle of civilization” and advocated a Marshall Plan for the environment, with financing of one hundred million dollars. The opposition of the Congress prevented him from starting the initiative, at least in the terms in which it had been designed initially, but it is significant that the maximum leader of the American scientific policy came to make these proposals, although they did not crystallize later.

Overall, the progress of the environmental movement during the last quarter of the twentieth century has been very significant, constituting one of the social movements of greatest interest in dealing with the risks and negative consequences of techno-scientific activity. Disasters like those of the Harrison and Chernobyl nuclear power plants, not to mention the opposition to the uncontrolled deposit of waste, or nuclear tests, are as many cases of study for the history of technoscience. The studies of science, technology and society should not only deal with the successes and successes, but also with the errors and failures of technoscience. In relation to the Gore environmental initiative, it would be worthwhile to study in detail the debates that took place in the Congress and in the scientific policy offices. It would be verified that the North American Government, which was the main agent driving macro-science at the time of the Second World War, has ceased to be so at the end of the 20th century, given the enormous power that private techno-scientific companies possess.

From an axiological perspective, we will say that the macroscience and technoscience of the 20th century have brought about the emergence of a new value system, ecological values. It is a value system reactive to technoscience, but little by little it acquires a certain weight in legal, political and social media, even becoming internalized by some techno-scientific companies. Initially, its defenders have interpreted this extension of the sphere of values as an extension of ethics, and that is why we talk about environmental ethics. In our view, it is not convenient to identify ethical and ecological values, without prejudice to their being interrelated. Traditionally, there has been a tendency to identify the sphere of values with ethics. One of the theses of departure in this book, already exposed in previous publications 98, affirms the specificity of the ecological values, in front of its habitual subordination to the moral values. Ecological values are not inserted, today, in the axiological core of technoscience, but their social presence is growing and little by little they are being internalized by many technoscientists. Many of the current controversies about technosciences have an ecological component, so it can be said that, even if only embryonic, the plural subject of technoscience tends to assume these new ecological values. If we add to the set of agents that we have just enumerated as components of the subject of technoscience an ecologist with good scientific and technical training, for example a representative of Greenpeace, we will improve our analysis of the structure of the techno-scientific activity.

In summary: the techno-scientific activity includes other value systems that, although they do not guide it, do seek to control and prevent its consequences and risks, serving as a counterweight to purely economic, military, political, scientific and technical values. The ecological values are a first example.

(i): Technoscience and society.

It also profoundly changes the relationship of technoscience with the public and society. In the case of science, the relationship between scientific communities and the public was first established through the context of education and dissemination. With technology, it focused on the context of application, considering citizens as potential users of technological innovations, once they are commercialized in the market. The gradual irruption and consolidation of technoscience has radically changed that relationship with the public, as there has been a crisis of confidence among citizens with respect to techno-scientific research and, in particular, with respect to expert reports or evaluations.

Opposition in the US to the Vietnam War and to scientific research for military purposes was the first example of this loss of credibility, which crystallized in the May 1968 movement. Protests on American university campuses not only chanted “no more research for the war “, but also attacked the” knowledge factories “that drove it 99. The same happened in relation to nuclear energy, which was finding increasing opposition in society, and not only by the memory of Hiroshima and Nagasaki, but also for the problem of nuclear waste produced by laboratories or the risks of accidents in nuclear reactors, some of which were part of the scientific macro-laboratories and were located on university campuses. Just as science had served to defend democracy in the 1940s, some investigations were now considered a danger to democracy, since they were exclusively used by military organizations. The partial militarization of the macro-science was criticized from multiple perspectives, penetrating criticism in society and reaching some scientists and academic leaders. Stanford University closed the Stanford Research Institute, which worked mostly for the Department of Defense. The MIT Instrumentation Laboratory completely changed its lines of research, orienting them to civil aviation. Only in the field of physics, projects financed by military agencies fell from 32 to 19% between 1971 and 1975, while the Department of Defense, which financed 20.1% of the total basic government investment in 1963, only he was in charge of 9 “3% in 1975. The effects of the crisis of the militarized mega-science were very real in the USA.

These protests had repercussions on an issue that would be central to the debate of the late 1960s: the demand for greater social and democratic control of scientific research. This was one of the pillars of the social contract of science established from the Bush report, according to which they left broad levels of freedom when choosing their research objectives. Even in military circles, the usefulness of basic research to manufacture new weapons began to be questioned. The famous Mansfield amendment (1970), which was approved by Congress and the Senate, not only required scientists to prove previously that their research would have real interest for the military institutions that financed them, but also instituted much more rigorous mechanisms of control of the expenditure, and even of the objectives of the research 100. This trend was not only shown in the USA, but also in other countries, such as Great Britain and France. On the whole, it can be said that in the 1960s some of the main postulates of the SCyT system that had arisen after the Second World War were questioned. With it emerged a new agent of the system, society itself, and did so in a distrustful and critical manner. The reorientation of research towards private companies in the 1980s was the way to avoid this social opposition to certain types of science, since the difficulties in the public sector began to be greater.

From the axiological point of view, this is the moment in which social values break out strongly in scientific activity, introducing new criteria for the assessment of technoscience. The crisis of the decade 1966-76 was the product of the emergence of new value systems, such as social, ecological and legal, which until then had had little relative weight in scientific media.

Let’s ignore what happened at the time of the crisis of militarized mega-science, waiting for more detailed studies, and let’s consider the relationship between society and technoscience today. Applying the distinction we usually use among the four contexts of techno-scientific activity (education, research, evaluation and application 101), it can be said that the relationship of citizenship with technoscience is much worse in the four contexts: many young people question more or less openly techno-scientific education, important sectors of society demand social control of techno-scientific research, distrust the reports and evaluations of experts in science and technology and, finally, openly answer some of the main techno-scientific innovations. In the background, a certain rejection of the new and growing power of technoscientists is being expressed. Social control and the democratization of science (in our case of technoscience) are two of the slogans that bring together those social forces that once looked at science with admiration, and today they contemplate technoscience with growing doubts, if not with a explicit rejection 102. This causes the techno-scientific communities, increasingly closely linked to economic, military and political powers, to concern themselves with the public image of science and technology, as shown by numerous programs of dissemination and dissemination of science and technology. technology in the US and in Europe. Technoscience has become a very important social power and it is not enough to techno-scientifically educate young people, as in the past. It is necessary to advertise science to improve the relationship between technoscience and the public. This is consistent with the business and marketing imprint that marks science and technology in our time. In short, public admiration for science has become a social concern for technoscience, with which the relationship with the public and society has radically changed. In many cases, this concern tends to turn into rejection, especially in those countries that are technologically dependent, that is, they do not have the human, financial or organizational resources to develop their own scientific policies. The gulf between the First and the Third World has an undoubted techno-scientific component. It is not strange that entire societies reject for the most part the expansion of technoscientific power to their countries, especially when this implies technological colonialization.

It is worth remembering that technoscience is not only oriented towards the control and domination of nature, as was the case in the Baconian sciences, but that it is primarily designed to control and dominate societies, as we have already pointed out above. This is the underlying reason why the relationship between technoscience and society is conflictive. In some cases, these transformations are well received by society. But in most cases there are reluctances, when not rejections. Some social sectors may support certain techno-scientific programs, to the extent that they expect to obtain benefits from them. Such is the case of the great biomedical (cancer, AIDS) or environmental research programs (anti-pollution products, bio-remediation, etc.). But many other lines of research and innovation raise doubts and distrust, if not outright rejection. Hence, techno-scientific companies have to include publicity and positive dissemination actions among their strategic lines. We are again faced with conflicts of values, whose resolution is not simple. Studies of social perception of science, qualitative or quantitative, are part of the techno-scientific activity, unlike modern science, which rarely paid attention to these problems. Knowing how to present technoscience to society in general, and not only to the upper layers of it, as was the case in modern science, is another requisite of techno-scientific activity, precisely because a large part of it is oriented towards the transformation of societies .

(j): Technoscience and international politics.

Macro-science emerged in the context of the Second World War and, as we will see in Chapter 4, was a purely national initiative, aimed at increasing US military, industrial, political and commercial influence. Its development in Europe in the first epoch of the postwar period was protected by the USA, reason why the scarce initiatives of European macro-science can be considered as an expansion of the North American macro-science. However, the consolidation of the USSR as a world power, increasingly opposed to the US, generated a strong scientific-technological confrontation between the two. At the time of the Cold War, there was no transfer of scientific knowledge between the two blocks, except in less important areas of research and through traditional academic channels. Until the 1960s, the separation between the two systems of science and technology was strict, considering communication of knowledge of strategic importance as a crime of espionage or high treason. This broke a venerable internationalist tradition of modern science, since macro-science was divided into two large blocks, practically isolated from each other. Scientists and engineers had to accept this situation, both on one side and on the other. Although in the era of modern science and industrial technology there had always been some secret areas in research, a situation like that of the 50s and 60s is unprecedented in the history of science. Therefore, we are facing another difference between science and technoscience, which should be briefly commented.

In the western bloc, the scientific and technological dependence of the old allies on the USA was strict during those years, as well as in the eastern bloc. Faced with the old rivalry between English science and continental science, or between German and French science, to mention two examples from the eighteenth and nineteenth centuries, the postwar period generated a reorganization of international science, agglutinated in two blocks strictly hierarchical. Besides, practically excluded from scientific and technological advances, the Third World remained. The geostrategic structure of the world had a direct reflection in the SCyT systems. Internationalist values declined rapidly in the face of the political, military, diplomatic and industrial confrontation that characterized the Cold War. Epithets such as “capitalist science” and “communist science” were common in those times.

The Second World War was taken advantage of by the USA to attract a large part of the European scientists who fled the Nazi persecution. During the postwar period, that emigration continued, since North America was the only Western country that allowed the development of those investigations that required large equipment and strong financing. This was one of the benefits derived from the decision to maintain the alliance between politicians, military, industrialists and scientists after the war, instead of dismantling the device that had been created during the war. The consolidation of the US SCyT system in the 50s not only had an effect on North American science, but also on an international level, placing the science and technology system in a position of clear international leadership, with a whole series of consequences: recruitment of brains, training of future leaders of European science, channeling of cooperation through organizations of strategic interest (such as NATO), etc. The transfer of technology, particularly military, was used as a currency to achieve strategic, political, economic and commercial objectives. Likewise, part of the knowledge was transferred in exchange for participating in the financing costs of the macro-projects of research, as we will see later in the case of the Hubble Space Telescope. In short, the power of science and technology was also shown as an instrument for foreign diplomacy.

However, until the 1960s, US scientific policy had not been systematized in its international aspects. The incorporation of science and technology issues into international politics, Kissinger’s work in Nixon’s time, the creation of the Tricontinental (1973) at the initiative of Rockefeller and Carter’s attempt to found an Agency for Scientific and Technological Cooperation, oriented to the Third World, were important steps in this direction. The latter failed, largely due to the reluctance of the large American business corporations. But the agreements of scientific-technological cooperation with other countries began to be part of the international policy of the USA. The agreements that Kissinger signed with the USSR and the Reagan administration with China, although they were of limited scope, showed that scientific-technological cooperation could have an important function at the time of ending the Cold War. Both initiatives were made with a view to the future, thinking about the huge markets that both countries offered for US companies.

The large industrial corporations and, subsequently, the companies of new technologies, had much to do with this expansion of scientific policy to the international arena, but during the 60s and 70s the initiative always had the Government. With the progressive emergence of technoscience, the situation changed. Some large companies, for example in the field of ICT (IBM, Hewlett-Packard, Microsoft, etc.), develop their own international R & D & I policies, transferring part of the production processes of other countries around the world. new technologies, although never the direction or the design. This is how the era of globalization and of companies-network 103 begins, coherently with the structural characteristics of technoscience.

The international expansion of American technoscience would require extensive and specific studies, sector by sector. Here we will limit ourselves to pointing out that the differences between the internationalism of modern scientists and the internationalization of current techno-scientific companies, beginning with the North American ones, are very large. First of all because new technologies transform the societies in which they spread, by changing people’s habits of life and their ability to act. The expansion of European science throughout the world took place through the context of education and dissemination. Technoscience, on the other hand, spreads from the context of application, precisely because it is a transforming activity of the world.

There have been many who see in this expansion of American technoscience a new form of colonization, centered on the appropriation and commercialization of knowledge, not on the natural resources needed for industry. This was denounced by the group of 77, of which most of the countries of the Second and Third World belonged. The thesis is very plausible. In any case, we should speak of techno-colonialism, to distinguish it from the European colonialism of the scientific-industrial era.

(k): The management of technoscience.

It is necessary to organize the techno-scientific work and manage the available human resources, not only at the time of research, but in all phases and contexts of the techno-scientific activity. Epistemic authority and technical knowledge are no longer enough. The techno-scientific agent or entrepreneur must know something about science and technology, but, above all, he must have knowledge about management of human and economic resources. Marketing and propaganda are characteristics that distinguish technoscience, notwithstanding that in modern science there have been important precedents of these skills. Many leaders of research teams develop most of their activity outside the laboratory, seeking resources for research, making public relations, in a word, selling the product obtained from research. This characteristic converts some scientists and engineers into knowledge entrepreneurs, with the peculiarity that they manufacture a product of great historical prestige, knowledge, traditionally considered as a good in itself. Knowledge management models form an important part of scientific policy, be it state or business.

In general, technoscience produces a considerable hierarchy within the techno-scientific teams, since not only research is required, but also development and innovation. The ultimate goal is innovation, not advancement in knowledge. The latter is desirable, but instrumentally. In addition, there is a high degree of opacity in relation to the specific objectives of the research activity, a good part of which is confidential or secret. A scientist who works in a techno-scientific company can completely ignore the ultimate meaning of the research he is doing. Ascribed to a chain of knowledge production, it only knows a small part of the research project in which it collaborates, especially in the case of macroprojects. Faced with the classical scientist, who faced problems that he knew and tried to solve, the techno-scientist develops a research work in exchange for an economic retribution, becoming another employee. Consequence of this are the labor and personal conflicts within the techno-scientific companies, which usually adopt the disguise of conceptual or technical divergences. Managing human resources is a must for any medium-sized techno-scientific company. On the other hand, union values (stability in the workplace, salary level, possibility of a career as a scientist, etc.) are inserted within the techno-scientific activity, especially if it has public funding. Once again we are faced with structural conflicts, derived from the new mode of knowledge production. The struggles for a fixed position in universities and research centers are usually canonical manifestations of this type of conflict, of great interest for the sociology of technoscience.

The complex chains of control and evaluation of the production of knowledge generate a huge bureaucracy, to the point that much of the time is spent writing projects, reports and proposals, increasingly complex technically. Experts emerge in this type of actions and new rhetorical skills to write this type of documents. Apart from the experts in research, development and innovation, techno-scientific companies require experts in administrative tasks. A good manager can be as important or more than a good researcher. It is another aspect of the entrepreneurization of technoscience, which often impatients classical scientists. Together, these companies are characterized by a high division of labor, since very different skills are required for the company to progress. The main objective is the progress and good functioning of the T & C company, which requires knowing how to apply economic growth, stabilization and reconversion policies, as the case may be. All this was unthinkable in classical science, guided by the ideal of cumulative growth. Techno-scientific companies last less than scientific institutions, due to the great pace of change and innovation imposed by technoscience. This happens without changing the paradigms of knowledge. The dynamics of technoscience is much more complex than that of science and has to be analyzed from multiple perspectives. Purely epistemic analyzes, which are only fixed in the rate of advancement of knowledge, are insufficient. The economics of science becomes a fundamental branch of science and technology studies, consequently with the fact that the production of technoscience becomes a new economic sector.

The economic sector S & T is having a great development in recent years, and not only in state institutions, but also in the private sector. Some techno-scientific projects are financed by venture capital organizations and there are some large techno-scientific companies that use the Bolsa as a way to obtain financing. Nowadays, 70% of the investment in R + D + i in the US comes from the private initiative, leaving only 30% in charge of the State and public institutions. This implies a radical change in the economic structure of technoscience, as well as in the evaluation criteria of techno-scientific institutions and companies. Modern science was financed by the States and by some patrons. Contemporary technoscience, on the other hand, tends to seek funding in capital markets, like any other large company. Public funding continues to exist, but its role is to catalyze initiatives. The creation of incubator companies is increasingly common in technoscience, contrary to the institutional model that characterized modern science.

Without going into more detail, we can conclude that both from the financial point of view and from the labor perspective, science and technoscience are radically differentiated, and not only by size, but above all by their different economic and work structure.

(l): Technoscience and law.

The techno-scientific activity is legally regulated in several of its phases and, when developed in a competitive market, gives rise to numerous legal problems and lawsuits. One of the most characteristic is the property of knowledge, which is specified when patenting innovations. The legal terms by which a patent is registered in the corresponding state offices are of great importance for the further development of the projects and for the achievement of benefits, which is why researchers who have achieved patentable results must contact experts in the field. laws that adequately define the ownership of knowledge. It should not be forgotten that, in the case of both macroscience and technoscience, research projects require the collaboration of various agents, for example academic, industrial, military or institutional. Fixing the distribution of ownership of acquired knowledge is a legal issue first and foremost. There are many cases in which the greatest successes of a project depended on the success when registering and marketing the patents 104.

Therefore, techno-scientific companies must rely on the collaboration of legal experts, which is unprecedented in modern science, where conflicts were usually resolved by arbitration commissions made up of prestigious scientists. These conflict resolution practices continue to exist, but in many cases they appeal to other types of instances. Conflicts between rival techno-scientific companies, for example, often end up in court. The same can be said of the privatization of knowledge, as we pointed out earlier. The registration, maintenance and management of patents, as well as intellectual property problems, become basic problems for the management of techno-scientific companies. There are also labor and hiring problems within them, which have to be resolved according to the corresponding legislation. This without forgetting that some private R & D companies choose to settle in countries with very weak state power, precisely to avoid these legal problems, including tax taxes. All this was unthinkable in the era of modern science and technology, so this is a new distinctive feature of technoscience. Some universities and research centers, and of course the R & D companies, have based their economic income for years on the exploitation of a few patents, which has made it possible to finance the subsequent research and make the research activity profitable, including research. basic

On the other hand, publicly funded research has to comply with a series of legal norms, both when submitting projects and when carrying them out and justifying the expense. The principal investigators have to commit more and more frequently to respect a series of ethical and environmental principles, apart from the strictly legal regulations. Taken together, technoscience faces a series of constraints (constrictions, ligatures) that are very different from those of modern science. The legal restrictions of techno-scientific research are very effective in democratic countries, which is why some techno-scientific companies opt for extraterritoriality, locating their headquarters, and even their laboratories, in countries with less political and legal control. Like many other great financiers, those who hold intellectual capital resort to procedures of dubious legitimacy to avoid such controls. Therefore, also in this aspect the techno-scientific companies tend to behave above all as companies, contrary to modern science or the pure patriotism and democratic spirit of many scientists at the time of the emergence of technoscience.

(m): Technoscience and values.

From an axiological point of view, the situation we are describing can be summed up by saying that apart from epistemic, technical and economic values (and in the case of the military, when we talk about discoveries or inventions with strategic importance), technoscientific activity is present other various subsystems of values: ecological, political, social, legal, etc. Some of these values are being internalized by the technoscientists, although reluctantly. Many of them yearn for the time of axiological autonomy, when their specific values clearly prevailed. Therefore, as we have already pointed out, within the technoscience not only a plurality of subsystems of values intervene, but also there is a structural conflict of values that did not occur at the time of science and industrial technology, or at least to a much lesser degree. We will say that technoscience is characterized by the existence of conflicts of values, which can adopt different modalities depending on the countries, the moments and the disciplines. Do not forget that technoscience is still highly effective when it comes to transforming the world, or to dominate nature, if you prefer. The problem is that this second objective of Baconian science finds important counterweights in those other subsystems of values that, although they have not been assumed by technoscientific communities, have a growing predicament in society.

It may be interesting that until now we have not talked about moral values. To the extent that technoscience is a human activity, questions such as honesty, truthfulness or trust are raised again and again. Being, in addition, an activity that transforms the world, ethical problems arise in function of the transformed objects. And since the technical actions are intentional, the greater or lesser morality of these intentions gives rise to significant ethical aspects. Therefore, moral values also have a role in technoscience, especially in some disciplines and moments. However, from the axiological perspective that we have adopted, there are other value systems that are much more significant than the moral ones, without prejudice to the fact that they can prevail and be decisive when making certain decisions. The same can be said of other value systems, such as religious and aesthetic. We will see in chapter 5 that axiological pluralism requires taking into account many values, some of which prevail in a few moments, but not always. There is no omnipresence of a single value system, not even one that is determinant everywhere.

(n): Technoscience and computing.

Modern science relied primarily on mathematics, while technoscience requires an additional formalism, computer science. The change is important, because the computer allows to represent and simulate various types of actions, and this recursively. The operational capacity of mathematics is great, but that of computer science is much greater. The tremendous rise of computer science and the technosciences that derive from it (cybernetics, robotics, artificial intelligence, telematics, etc.) is not an incidental detail, but illustrates another distinctive feature of twentieth-century technoscience. The two main methodological pivots of modern science were mathematics and the experimental method. Computer science and simulations are the two major methodological innovations of the twentieth century, whose irruption, development and consolidation mark the transition from science to technoscience from the point of view of formal languages and methodology.

Mathematical models allow to analyze and discover new relationships between the objects studied. The same happens with computer science, with the difference that it is applied to very diverse systems, and in particular to the technological systems themselves, which can be computer simulated. As Aracil indicates:

“The computer has the virtuality of being able to be programmed so that its behavior is what establishes the program. By changing this, we have a new behavior. In this way, the computer can imitate or simulate the behavior of any machine; its possibilities, in this order of things, are immense “105.

Given any machine, we will call infomáquina to your computer simulation, if possible. In principle, practically all mechanical devices have their corresponding infomachines. The same happens with thermodynamic machines and, more importantly, with a new type of artifacts that emerged in the 19th century, one of whose examples is the Watt regulator. It was Maxwell who took care to theorize these centrifugal regulators and showed the importance of their valves, whose opening or closing gradually allowed to maintain the speed of the steam engine approximately constant. Therefore, some of its parts were not designed to generate energy, but to introduce information into the machine itself, so that it could work automatically. Watt’s regulator did it mechanically, but soon it was found that electricity was the ideal instrument to transmit information. This type of devices, whose function is to introduce information on the state of the machines, were essential for electricity distribution networks and telephone networks in the nineteenth century, as well as for the automatic control technologies that subsequently gave rise to Robotics 106. The servomechanisms also incorporate these information feedback loops, which are common in computer tools:

“It is known by feedback (feed back) the process by virtue of which when performing a global action, succession of partial actions, in order to reach a certain objective, information is continuously fed back on the effects of previous actions, so that the successive actions take into account the results of those past actions “…” The feedback mechanism consists of a successive chain of action – result (state) – feedback of information – analysis of the discrepancy with the objective – new action, in its case, and so on “107.

Computer machines can carry out these loops without any problem, because they are based on the continuous feedback of information through programming languages. This allows the actions to be iterated by modifying the initial and contour conditions, which gives access to a new experimental mode, based on computer simulations. In philosophical terms, the information technologies greatly expands the field of possible actions, which is very different from that of possible worlds. By modifying parameters and programming, it is possible to simulate many more actions and processes than with mathematical models. For example, you can represent the possible expansion waves of a bomb, the movement of several aircraft in an airspace, the possible trajectories of a missile, the destructive effects of a predator on a school of fish, the foreseeable evolution of a harvest , the situation of the upper layers of the atmosphere, the evolution of an economy based on macroeconomic or other data, the operating results of a company, etc. The computer allows a new type of experimentation and prediction, which is not deterministic but probabilistic. All this is essential when calculating the effects, consequences and risks of techno-scientific actions, both because there are no other analytical tools available and, above all, because the feedback of the data makes it possible to carry out multiple experiments of a virtual way Before operating and experimenting materially, computer simulations allow the analysis of multiple scenarios or possible states, which implies enormous savings in economic, ecological and time costs. Hence, computer science is the main instrument for investigating the domain of possible actions, including the actions of the multiple infomachines that reproduce the behavior of real machines. On the other hand, since the machines are a type of systems, the computer science also allows to investigate the evolution of other types of systems (physical, chemical, biological, economic, social, urban, etc., including the SCyT systems of scientific policy- technological). As Aracil points out, “we can make of it a potential replica of any system we try to study” 108. Since in this work we have opted for a systemic ontology when studying technoscience, it is logical that we attribute great methodological importance to the computer science, to the being the most suitable formal instrument to study the diverse systems, as much from a static perspective as dynamic.

The emergence of computer science in the second half of the twentieth century has a great philosophical and scientific importance, among other reasons because it allows to represent complex systems, which are not treatable by the resources of classical mathematics. Von Neumann designed the ENIAC and the EDVAC in order to solve nonlinear problems that, being very important for physics, were not approachable through the Differential and Integral Calculus, nor through the Algebra procedures. On the other hand, computer science has allowed the development of cybernetics (N. Wiener) and has generated very important models for simulation in systems dynamics (Prigogine). As indicated by Javier Aracil, by system is meant “a complex entity, consisting of properly coordinated interaction parts” 109. Now, “those parts have no meaning except in so far as they are integrated into the higher order unit that is the system itself” 110. Well, “to understand the functioning of a system is usually understood to know how the parts of which it is formed influence each other, so that the proper coordination of these influences gives rise to the global functioning of the system “111. This is possible thanks to the construction of computer simulations and models. Once analyzed the behavior of a system, the computer can build another artificial system (called model) that has the same components of the system studied and behaves similarly:

“The study of a concrete system, through the dynamics of systems, leads to the construction of a model that is susceptible to being programmed in a computer; in this way, in the latter there is a replica or copy of the concrete system under study: with the help of the computer, the evolution over time of the magnitudes considered relevant to the studied system is obtained “112.

Since science has been busy studying increasingly complex systems, computer science has become indispensable for scientific research. In section II.3 we will mention many examples of this omnipresence of information technology in today’s technoscience. Speaking in general terms, it can be said that the different computer tools generate a new representation of knowledge, on the one hand, and also of the change and evolution of physical, biological systems, etc., something that was not possible with traditional mathematics, centered on the continuous, not on the discrete. With greater or lesser precision and adequacy, computer science can represent systems of great complexity (physical, chemical, biological, social, economic, etc.), thus expanding the field of scientific research. The same applies to technological systems, which have been radically transformed by the emergence of information technology, especially as regards the control of their operation. The automation of the operation of the machines is the great achievement of computing, having been incorporated into the most diverse economic and social sectors. Well, the same happens in the case of scientific activity, most of which is now automated, and therefore controlled by automatic devices.

Computer mediation is one of the main requirements of the emergence of technoscience. Compared to the mathematized sciences (to a greater or lesser extent) of the modern era, the vast majority of technosciences are computerized, and therefore mediated by technology in the own representations of scientific knowledge, as well as in the operations that are carried out out with the data. Technoscience is based on a new formalism, apt to represent actions, not just knowledge. Unlike simple macroscience, technoscience itself requires the computerization of scientific and engineering activity. The notion of technoscience, understood as information science, or computer science) is more precise than that of macroscience, because it takes into account factors more relevant than simply increasing the size of science. In the step from science to technoscience not only changes the size. Also, and above all, the form. And not only the way of representing knowledge, but above all the way to act scientifically.

(o): Technoscience and the information and knowledge society.

Macro-science emerged as a development of society and, as we saw, meant the industrialization of scientific knowledge. Technoscience, on the other hand, is linked to a new form of society, which has begun to take shape in the last two decades of the twentieth century: the information and knowledge society. There are many differences between this and the industrial society, but the most important for our objective consists in the new economic status of validated and contrasted knowledge, and in particular of scientific knowledge.

Information and knowledge become a new source of wealth and power. Therefore, scientific knowledge becomes a basic good for large companies and power agencies. Instead of controlling, accumulating and manufacturing raw materials, in order to obtain benefits as a result, the economy information is based on the discovery, elaboration and commercialization of knowledge deposits. Basic science thus acquires an enormous economic and political relevance, since it is a great source of wealth and power. The economic, political and military powers tend to appropriate scientific knowledge, generating for it Agencies and Departments of research, development and innovation. The scientific and technological communities are capable of generating noo-riches, to use the terminology of Sáez Vacas 113. The development of industrial society and the great wars of the twentieth century clearly showed that this form of wealth is one of the engines of the economy and of society. The powers of the new type of society are clear that the production, management and profitability of validated knowledge is essential for their own interests, and therefore they are introduced in the field of noogies, until then cultivated basically by scientists and engineers.

The transition from macro-science to technoscience occurs with the emergence of the information and knowledge society. The research macro-projects, which are the engine of the informational economy, are still being maintained, but exploitation actions from smaller areas of the noosphere are also promoted. The new scientific-technological system, which had been configured around a few disciplines, is generalized to all areas of science and technology, be they small or large. Technoscience is not a matter of large scales. Small research and innovation projects become very important, as long as they are designed and managed according to the organization model of the activity we saw in the case of macro-science. Small knowledge mines can be just as profitable as large ones, and even more so. Technoscience is based on the systematic exploitation of scientific and technological knowledge reservoirs, to the extent that these veins, whether small or large, have considerable value in the information society.

From an axiological perspective, the novelty lies in the following: knowledge had been considered as an epistemic good. No scientist of the modern era had doubts about it. It is necessary to seek knowledge, because this is a good in itself, regardless of whether it is applicable or not, or that breaks with previous systems of knowledge. With the advent of technoscience, information and knowledge remain epistemic goods, but they become technological, economic, military and political goods. Put another way: scientific knowledge is valued in terms of new value systems. Consequently, doubts arise about the universal goodness of said knowledge. A scientific discovery with strategic value in the military field, for example, is an undoubted good for those who possess this knowledge, and at the same time an evil for those who do not possess it and bear the consequences of its application, once developed technologically and implemented for the battlefields. The Hiroshima and Nagasaki bombs are a point of no return for those who naively believed that knowledge is always a good. In other words: techno-scientific knowledge has ceased to be a good in itself to be a good from some points of view and a bad from others.

II.3.- Plurality of technosciences.

Just as in the nineteenth century a plurality of sciences was differentiated, some traditional (mathematics, logic, astronomy, medicine, physics, chemistry, biology, geology), others new (economics, sociology, psychology, anthropology, etc.), On the basis of which the scientific building of the 20th century was organized, during the 21st century it will be necessary to distinguish between these disciplines and their corresponding technosciences: techno-mathematics, techno-logic, techno-astronomy, technophysics, technochemistry, technobiology, technomedicine, technogeology, techno-economics, techno-sociology, techno-psychology, etc. Since we have affirmed the emergence of a new modality of scientific-technological activity, it is necessary to check whether this change has occurred in the various disciplines, as well as when, how and where. This would require very detailed studies of the evolution of each scientific (and technological) discipline, a task that we do not intend to face.

In this section we will list multiple examples of specific technosciences, even if only in a very summary way. With this, the concept of “technoscience” will acquire an extensional determination, not only intensional, as it has been up to now. We will limit ourselves to briefly mention some of the main examples, without trying to systematize the study or the development of each of the technosciences.

(a): Tecnomathematics.

Although the macrociencia arose historically in the field of physics, we will begin our examination with the tecnomatemática, and this for three reasons. First, because the ENIAC project was one of the first canons of macro science. Second, because computer science can be considered as the main modality of mathematical technology. Third, because the passage from mathematics to techno-mathematics illustrates well the difference between macroscience and technoscience. Technological mathematics can be macro-, but also micro-, while being mediated by computer technologies. Since we have stressed the importance we attach to information technology in the development and consolidation of technoscience, its own emergence requires special attention.

Technological mathematics emerged as computing sciences, focusing on one of the most traditional tasks of mathematicians: the numerical and symbolic calculation. From the 30s there was a great effervescence in this field. In 1930, Vannevar Bush built a differential analyzer at MIT that solved important equations for the study of electrical circuits. The German Konrad Zuse devised a universal calculator, the Z3, completed in 1941. It was a small machine with a band reader, a console for the operator and two cabinets with 2,600 relays, which could do several mathematical operations, for example multiplications and square roots with 22-bit numbers. The initial values had to be entered by hand, so it showed important technical deficiencies. The users of these machines were scientists, but also military: Zuse Zuse was used in 1943 for operations against allied ships in the Mediterranean 114. Another great project that should be mentioned was the MARK I, initiated by Howard H. Aiken at Harvard in 1937. He introduced a record of the data, which would later become the memory of the computers. Funded by IBM, the MARK I was introduced in 1944 and offered immediately to military authorities for its calculation power. All these machines were electromechanical. The introduction of vacuum tube technology (Atanasof and Berry, with its ABC of 1939) made it possible to create the first electronic calculators, as well as the digital representation of numbers, as opposed to the decimal.

The ENIAC of the Moore School of Pennsylvania, started in 1943 and perfected in its design by von Neumann in 1945, managed to integrate several technical improvements that emerged during the 1930s. It was built by Eckert, an engineer, Mauchly, a consultant, and Goldstine, in charge military of said project, which was classified as secret (project PX of the Office of Ballistic Material). The ENIAC had 17,648 vacuum tubes, 70,000 resistors, 10,000 capacities, 1,500 relays and 6,000 manual switches, making it a large and complex machine, whose operation required many technical skills. If a single tube was damaged, the calculation was interrupted and we had to start over. It cost a fortune, 500,000 dollars from that time, but it worked at great speed and was both programmable and universal, that is, applicable to various types of calculations. Its consumption of electricity and its emission of heat was enormous, so it had to be continuously cooled. After the incorporation of von Neumann to the equipment, the design of the apparatus improved a lot, as well as its automatism 115. Thus EDVAC emerged, direct heir of the ENIAC, and after it a saga of computers designed according to the “von Neumann architecture”. Funded by the North American Army, it can be considered as the first computer in the current sense of the term, and therefore as the initial paradigm of macromathematics. The main novelty was that the program that ordered the execution of the calculations was recorded in the same machine, that is, the original idea of what we now call software: “the new machine, contrary to its predecessors, no longer calculated: it was binary information, which allowed it, indirectly, to perform calculations “116. It can be said that, if the ENIAC was the canon of macromathematics, the EDVAC foreshadowed what we call technomathematics, insofar as it was a machine designed to process information , not only to make calculations 117. Hence the importance that we attribute to the ENIAC-EDVAC project to investigate the origin of macromathematics and techno-mathematics.

We will not expand on historical details, which are now perfectly accessible. From the ENIAC-EDVAC project, we are interested in emphasizing, on the one hand, its enormous size and complexity, on the other hand, its great efficiency for quickly computing trajectories of projectiles and shock waves and, of course, its military project character, with an important industrial and engineering component. . But we must not forget the deep scientific knowledge that von Neumann contributed, both in the field of physics and mathematics and in the emerging theories of computation, some of them linked to neurophysiology. Significantly, after the end of the world war, important divergences arose among the members of the team that had designed and built it. Eckert and Mauchly wanted to market the machine: in fact, they ended up founding UNIVAC. The Army built new, more powerful prototypes for military use. Von Neumann insisted on using it first of all for scientific research and devoted himself to giving lectures all over the world to make the invention known. The conflict ended up in courts and later in a tough commercial competition between IBM and UNIVAC. Therefore, already at the dawn of the techno-mathematical appeared many of the distinctive features we have pointed out, although here we will not study them in detail.

In subsequent decades, this “techno-thematising” trend continued to develop. Relatively complex branches of mathematics such as Algebra and Differential and Integral Calculus were absorbed by the technomathematics. Today there are numerous mathematical packages (Macsyma, Reduce, Mathematica, SPSS, etc.) that allow you to perform automatically operations that mathematicians took centuries to master, such as solving algebraic equations, differential calculus, resolution of integrals or the statistical distributions. The same is true of Geometry, since computers make it possible to trace and solve geometric figures much more easily and quickly than with classical techniques. New modalities of geometry have also emerged, such as the Turtle Geometry, which can be rigorously called technogeometries (or infogeometries). All that mathematical software is based on the mathematical theories themselves, but it considerably increases the ability to operate and, above all, generates new mathematical objects, for example fractals. Computers carry out many mathematical actions better than people, which does not imply that everything can be done by computers. Technological mathematics does not imply the disappearance of mathematics. What happens is that a new way of doing mathematics has appeared.

The examples abound: in Theory of Numbers a new branch has arisen, the Computational Number Theory, that has great utility for the cryptography and to approach some classic problems, like the Riemann conjecture. Many of the problems of Elementary Algebra can be addressed through Computer Algebra computer programs, which does not prevent further investigation of other algebraic structures with traditional methods. The same is true of Mathematical Analysis, an area in which there has been great progress in computerization, without it being exhaustive, much less. One of the most significant examples of technomathematics was the demonstration of the theorem of the four colors in Topology, mainly because it introduced radical changes in one of the most typical actions of mathematics: the action of demonstration, whose result is demonstration. An important part of this demonstration can only be carried out by means of the computer, so that the technological mediation also reached the demonstrations 118. On the other hand, despite the efforts that have been made in artificial intelligence for the automatic demonstration of theorems, This is far from being achieved, except in simple cases. However, investigations related to the automation of geometric demonstrations, for example, have brought important advances in other areas of technoscience, such as robotics, machine vision or solid geometry 119.

A third canon of technomathematics was the creation in the 80s of a new mathematical language, TEX, designed by Knuth and widely spread throughout the world. Nowadays, mathematicians write in some of the different variants of TEX, maintaining a computer language common to all of them. That technique of mathematical info-writing has come to be added to the various sign systems used by mathematicians, not to eliminate them. A fourth example is infographics (Sutherland, 1963) and many more could be mentioned. The history of techno-mathematics remains to be done, insofar as it does not fully coincide with the history of computer science, although both have arisen from the same embryo.

Influence not only occurs in one sense, from technologies over mathematics, but also in the opposite direction. The enormous development of computer algorithms, for example, has generated new mathematical theories: Algorithmics, Theory of Recursive Functions, Theory of Computational Complexity, Artificial Intelligence, etc. Not only are there computer technologies, but also computer science. Technoscience not only generates new technologies (such as Robotics), but also new sciences and new theories. It is one of the reasons to call it technoscience, not simply technology.

Although in principle the technological mathematics required large computer equipment, something that continues to happen (CRAY computers, interconnection of multiple computers through the Internet to investigate certain mathematical problems, etc.), it is no less true that the technological mathematics are currently developed with relatively computer equipment. little ones. Therefore, size being a distinctive feature between science and macro science, it is not the main one between science and technoscience. Much more important is the profound change that computer science has brought about in mathematical activity, part of which would be unfeasible today without that technological mediation, beginning with the action of writing and publishing. Throughout history, whenever a new mathematical formalism has arisen, changes have been enormous in almost all sciences. This is the case of the emergence of new computer formalism, which has been the main factor in the emergence of the mathematical-mathematical system, together with the profound transformations that the mathematical communities have undergone, part of which have become techno-mathematical companies. Cryptology and artificial intelligence are two of the canonical examples, but many others could be provided, such as Statistics itself, whose development, application and teaching are impossible without computer help today.

(b): Tecnoastronomy.

It is another of the great examples of technoscience, especially since it affects one of the oldest scientific disciplines, together with mathematics and medicine. Just as the Galileo telescope revolutionized 16th and 17th century astronomy, so new technologies of observation, computation and data representation have radically modified our conception of the cosmos and, moreover, astronomical research. Throughout the twentieth century there has been a profound revolution in astronomy, both from the theoretical point of view and from the praxeological perspective. In our view, it is a techno-scientific revolution, first of all aroused by the changes in astronomical practice, and more specifically by observation devices, which are nowadays enormous equipment that explores space from sidereal distances.

The first branch of astronomy that took the step towards macro-science was radio astronomy 120. However, we will focus on optical astronomy, and more specifically on the Hubble Space Telescope program, because it better illustrates the passage from astronomy to macroastronomy, and then to technoastronomy. The great telescopes (Wilson, Palomar, etc.) existed before the Second World War, and it can even be said that there have always been telescopes in the history of astronomy. The techno-astronomy of the Hubble project does not depend on the size or cost of the instruments, both of which are very large, but on a profound change in the research practice, as we shall see below. We are also interested in the fact that said macroproject was driven by “external” instances to the community of optical astronomers, who were very skeptical at first, if not critical 121.

The techno-scientific agent that drove the Hubble project since 1970 was NASA, the North American Scientific Agency specializing in space research. The project was hard debated for three years and finally approved by the White House and the US Congress, although its development until 1990 suffered many vicissitudes, and in particular a budget stop in June 1974. The reason invoked was that it was not one of the four projects selected as priorities by the National Academy of Sciences. Indeed, in 1972 the Astronomy Committee of the Academy of Sciences had not considered it urgent for the decade of the 70, relegating its realization to the 80s, and as a second priority. There were other alternative projects, such as the space probe to Jupiter (Galileo project), which was of particular interest to planetary astronomers. However, a lobby formed by NASA, the companies involved in the construction of the space telescope and some concrete astronomers (Bahcall, Schwarschild and Spitzer, in particular the latter), managed to overcome the skepticism of the majority of astronomers 122, agreeing on some modifications in the initial project. The House of Representatives had demanded international co-financing, at which time the European European Space Agency (ESA) entered. From the scientific point of view, the initial design was oriented to stellar and galactic astronomy, of great interest for cosmology. A technical change, the replacement of the photographic detector initially foreseen by another one that was sensitive to the red areas of the spectrum, allowed that the design of the Hubble was more suitable for the observation of the planets of the solar system, condition required by another committee of the Academy of Science. Subsequent pressures in favor of the Galileo Project made it necessary to seek a compromise solution again. As we will see in chapter 2, this is one of the ways in which technoscientific controversies develop: by struggling for the priorities of one or other macroprojects among the various scientific sub-communities, which seek allies in government agencies, parliamentarians, politicians, committees , etc., in order to take forward the initiatives that interest them.

The space telescope was started by NASA in 1977, hiring most of the work to American private companies. It was launched into space in 1990 and since then it has worked reasonably well. Since the project of a space telescope emerged in the 1960s, the Hubble project completely covers the transition stage from macroscience to technoscience in the field of optical astronomy. The estimated cost of the first project (1965) was one trillion dollars. The real cost was much higher.

The main objective of the space telescope was to avoid interference from the atmosphere for optical telescopes and increase the degree of precision of the observations. Optical astronomy, unlike radio astronomy, had always been limited to the visible area of the electromagnetic spectrum. The space telescope, in change, can observe in the range of the spectrum that ranges from 120 nanometers to 1 millimeter, greatly expanding the observational capacity of the discipline. It was an important technological improvement that allowed to expand a capacity for scientific action, observation. Although Hubble did not achieve the observational capacity for which it had been designed, due to the appearance of a little-studied phenomenon, the spherical aberration in the enormous lenses it was provided with, however, considerably improved optical astronomy, contributing positively to the development of cosmology. Numerous scientific theories have been contrasted thanks to Hubble. Despite this, the scientific community, with some exceptions, did not see at first the need to carry out such a large economic investment, since terrestrial telescopes in good atmospheric conditions could be more powerful, although they had less capacity for resolution. In summary, the epistemic expectations raised by the space telescope did not justify, in the opinion of the optical astronomers, the enormous investment or the disadvantages derived from this dependence on a single device, which would then be very difficult to improve technically, because it is in space , not on land. On the other hand, no scientific institution, however powerful, was able to assume the high cost of the operation. The leadership of NASA was absolutely necessary for the project to be carried out. Already in the design phases of Hubble, NASA decided to turn Hubble into a “national facility”, that is, put the many data that Hubble would get when it was available to all American astronomers, and not just a few. institutions. This decision made the cost of the project on the Federal Administration and NASA itself gravitate, but it contributed decisively to the Hubble project, then called Large Scale Telescopy, having greater acceptance among optical astronomers, who were promised large amounts of data. for future research, including planetary astronomers. Optical macro-astronomy, then in the design phase, promised to generate new knowledge, as long as the technology worked. The project began to have more followers, compared to the tradition of land-based and fixed telescopes. As Smith underlines, “in the early years of NASA, research in space astronomy was the subject of a small number of principal investigators and their associated teams, located in a university or laboratory” 123. The Hubble project radically modified this an atomized research culture, forcing the creation of research networks with universities and research centers interconnected through Hubble.

Obviously, NASA had to solve the problem of data transmission from space to land, for which the creation of telematic networks was essential. In a word, from the observatory located in a certain institution, we went to the observatory-network, with a large number of astronomers connected to Hubble to access the data. The computerization of astronomical research was also necessary, as well as the signing of collaboration contracts with NASA by the universities and astronomical observatories beneficiaries.

We verified with this that this macro-scientific project was becoming technoscience in the full sense of the term during the phase prior to its realization, that is, during the construction of Hubble. In its design phase in the 60s and early 70s, Hubble and the other projected space telescopes were only macroscience. As the project was being configured, new needs emerged, not only scientific or technological, but also financing, collaboration and, in particular, changes in the organization of the activity astronomical A whole research culture was transformed thanks to the Hubble project. When the telescope was launched into space, the community of optical astronomers had been radically transformed. He had become part of a techno-scientific company, led in this case by a Government Agency. Similar processes occurred in other sectors of astronomy, although here we are not going to deal with them.

Hubble has been decisive for the astronomical research of the late twentieth century, for having generated a lot of knowledge, both observational and theoretical. Verifications, checks and falsification of conjectures have been the order of the day since Hubble was launched and was operational in the 90s. But the important thing is that, before new knowledge emerged, scientific practice had been transformed radically This is one of the main theses that we maintain. There are many works of cosmology in which the Hubble Space Telescope is mentioned again and again as a decisive instrument for obtaining astronomical knowledge. On the other hand, studies on the previous change in the structure of astronomical research, which had been caused by this project long before the apparatus was operational, are scarce. The techno-scientific revolution in optical astronomy was driven by the project of the space telescope, not by its epistemic results. Once that revolution was realized, great theoretical changes emerged. When we talk about technoscience it is necessary to analyze first the changes in scientific practice, which are what characterize this new type of revolutions. Regardless of the effect that the data from Hubble have had for the alternative cosmological models that were in dispute at the end of the 20th century, the techno-scientific revolution had occurred before in that discipline. The implantation in optical astronomy of a new mode of production of scientific knowledge is the distinctive sign of techno-astronomy as opposed to traditional astronomy.

It should be emphasized that large techno-astronomical projects, such as Hubble, not only generate new observation instruments, but also require new transport, telecommunications and information processing systems. The lenses of the current astronomers (who are called astrophysicists) are not fixed, but mobile, and are transported thousands of kilometers from Earth’s space by space rockets. This allows to improve the observation and access to astronomical objects that were previously unobservable, as well as to detect new phenomena. For this it is essential that the data obtained by the space telescope be sent to Earth in a fully automated way and through telematic networks. There is no possible Hubble or exploration of planets and galaxies without advances in the field of computing and telecommunications. ICT is one of the requirements of techno-astronomy, and in general of techno-scientific research. Therefore, classical astronomical actions and the data obtained from them are completely mediated by the different technologies that allow them to be obtained and transmitted to terrestrial computers. We are again facing a clear example of technoscience, which has brought with it a huge theoretical development, not only technical. It must be said that a good part of contemporary astronomy has become a techno-astronomy and that the various cosmological theories proposed by theoretical physicists are all based on technodata or empirical techno-evidence. The notion of empirical evidence is technologically mediated, and this necessarily, as well as the technical-mathematical demonstrations. A new argument, this time epistemological and methodological, to support the distinction between science and technoscience.

We must also highlight the transdisciplinary nature of techno-astronomical research. The construction and operation of the techno-observatories depends on a multitude of scientific and technological disciplines, but the results that derive from such a project not only affect astronomy, but also other branches of science and engineering. The transdisciplinarity and the symbiosis between science and technology is one of the distinctive features of technoscience, as opposed to the disciplinary compartmentalization of the sciences and technologies of the Modern Era. Technoastronomy provides multiple examples of this, as do other technosciences. Suffice it to think that, under the influence of techno-astronomy, the term “geology” is no longer the most appropriate, since it is now possible to make “geological” studies of objects that are not Earth: the planets and their satellites, comets, the stars, etc.

Technoscience also leads to rethinking some classical philosophical problems. We will mention an extremely simple example, which we think is sufficiently illustrative. Suppose the statement “there is water on Mars”. Is true or false? To elucidate this issue, technoscience is essential, and in particular the Hubble project, since spacecraft have to be moved near Mars, eventually depositing robots on their surface, completely automate the action of observing, transmitting the data obtained to Earth. through telematic networks, etc. This done, the astronomers, who will have to know in depth the techniques of computer representation of the data transmitted by the Hubble, will call the chemists to verify the truth or falsity of the statement and, where appropriate, study the composition of the Martian water. , which will have extreme interest for the “marteólogos” and for many other scientific communities. A new sample of the transdisciplinarity of the techno-scientific researches and of the radical change that technoscience induces on the notion of “empirical knowledge”, thanks to the previous change of the scientific practice.

(c): Tecnophysics.

Physics was the scientific field where macro science first developed, with the various Radiation Laboratories, the Manhattan project and the construction of cyclotrons. It was also a pioneer in the restructuring of scientific activity. The macroprojects of the 40s and 50s had a strong industrial component and, in terms of the links with scientific policy, many prestigious physicists dedicated themselves to it and ended up becoming real professionals. Some Departments and Research Centers of Applied Physics were the first examples of industrialization and entrepreneurship of science. As a whole, it can be said that physics abounds in macro-science and technoscience examples, both in the US and in other countries. An in-depth study of macrophysics and techophysics during the twentieth century would require several books, so here we will limit ourselves to briefly mention some illustrative examples, leaving for further research a more detailed analysis of the technophysical revolution of the twentieth century. We will focus on the first era, macrophysics, for having been decisive in the change of structure suffered by scientific research at the time of the Second World War.

The Manhattan project is the main example, which is why we will focus on it. From a financial point of view, it was the first great macro project of the 20th century, second only to the great programs of space exploration. It is estimated that in the period 1942-45 the US invested 2 million dollars from that time in its development, that is, more than 100,000 million dollars to the value of this currency at the end of the century. It was a most secret military project. In its development collaborated theoretical physicists, experimentalists, chemists, mathematicians, engineers and numerous industries. Developed at a dizzying pace, it experienced important changes in function of the scientific discoveries that were made as it was progressing. From the beginning we worked on two projects, one aimed at the manufacture of a uranium or plutonium fission bomb, the other towards an implosion pump. At first, the fission bomb had the priority. In 1944 the plutonium bomb was given a higher priority and research began on thermonuclear pumps whose possibility had been suggested by Teller, one of the physicists involved in the project. The final results were very satisfactory for the promoters of the project and for many of those who joined it. Scientific knowledge advanced enormously and innovative technological developments arose: nuclear physics has generated a new source of energy, unknown until the twentieth century. Some companies became millionaires thanks to the Manhattan project. The US military scored an undoubted success, which has marked the strategies of the armies throughout the twentieth century: owning the atomic bomb has been the goal of all the great powers. In summary, from the perspective of the promoters of the project and of the various groups that actively participated in it, the results were very satisfactory.

The valuation of these results changes completely if we place ourselves outside the core of the macro-science. The human, social and ecological damage in Japan was immeasurable with what every other weapon of war had produced throughout history. The further development of nuclear weapons by the USSR led to the balance of terror, a situation that has not been unprecedented in history, given the magnitude of the disaster that could have produced a nuclear war. The moral and religious valuations of the bombings were clearly negative, but they did not have any incidence, not even to stop the development of the arms race. The Manhattan project is a clear example of the de facto primacy of other value systems, apart from ethical and religious values. Few examples are so clear to show that macroscience and technoscience generate deep conflicts of values. The Kuhnian notion of incommensurability between theories is irrelevant when analyzing this new form of contradiction, which occurs in practice and with terrible consequences for people, countries and the environment. As we will see in the next chapter, the Manhattan project is one of the canonical examples of the new techno-scientific paradigm. Never has the human being demonstrated such ability to transform the world, in this case destructively. The techno-scientific knowledge irrefutably showed its enormous potential by taking the destructive capacity to hitherto unsuspected levels.

It is important to remember that Los Alamos was a military institution in which some civilian scientists had great power. It was the first practical example of the effects that the social contract can have among politicians, scientists, engineers, industrialists and the military. Internally, the structure of the various departments and teams was strictly hierarchical. The Laboratory Director, Oppenheimer, had the power to transfer scientists from one team to another, depending on the priorities of the project. Within each team, scientists and engineers collaborated closely. There was a Governing Council and another one of Coordination between the different Departments, which at the beginning were four: Theoretical Division, Chemistry and Metallurgy Division, Experimental Physics Division and Engineering and Ordnance Division 124. By its own denomination, it was clear the military nature of the research, as well as the type of scientific-technological personnel involved. Groves and Oppenheimer followed from the beginning a pluralist strategy: although the line dedicated to fission was a priority, alternative lines of research were also supported, provided that they could lead to result of producing an atomic bomb that, if necessary, could be manufactured in series. For this second objective, plutonium seemed preferable to uranium, because it could be manufactured in a nuclear reactor, whose construction in Chicago was hastily entrusted to the private company Du Pont. This great work of engineering was crucial for the development of the project, because thanks to the construction of said nuclear reactor, the phenomenon of spontaneous and relatively frequent splitting of plutonium (once a month) was discovered, which became a new topic of scientific research. The industrial production of plutonium, necessary for the Manhattan project, made possible the study of a new physical fact, hitherto unknown. As L. Hoddeson states in commenting on this discovery, “this spontaneous fission experiment is one of the most important case studies in the history of physics, because it illustrates how a purely scientific result could change the course of history” 125. minimum, changed the priorities of the Manhattan project research. The small group dedicated to studying the implosion bomb went from five members to fifty in a few months.

As explosives experts (Kistiakowsky), fluid dynamics (von Neumann), computation (IBM, ENIAC) or spontaneous fission (Berkeley group, led by Segrè) were needed, they were immediately signed up for project 126. Meanwhile , chemists worked on the separation of plutonium 240. Another feature of the Manhattan project was the parallelism between different lines of research. When there were still important problems to solve (theoretical, instrumental, industrial production of plutonium, previous tests, etc.), the other teams continued their investigations independently. The coordination of the stages and of the foreseeable achievements was fundamental for the success of the project, as well as the flexibility when modifying the priorities and keeping alive alternative lines of investigation, in case any of them failed. The final objective, strictly military, prevailed over the convictions that the scientists involved in the project could have about the most accurate theoretical assumptions and about the apparently most promising lines. Any theory was valid, provided that there was a glimpse of possibilities to achieve the main objective. Another clear sign of subordination of the epistemic objectives of scientists to the main purposes of the project, as well as the instrumentalization of scientific knowledge for the achievement of a military objective.

On July 20, 1944, the Managing Board of the Manhattan project announced that, from that date, “all the priority had to be given to the implosion program; at the same time, nothing would be left of the alternative program “127. As a third priority, Oppenheimer authorized Teller to investigate the question of thermonuclear bombs. As a consequence of this decision, two new Divisions were created in the Manhattan Project: the G (gadget), dedicated exclusively to the theoretical problem of the implosion of plutonium, and the X (explosives and complementary investigations on the implosion). Some scientists and engineers were transferred from the previous Divisions to the new ones, but without eliminating any. The new priorities did not imply the abandonment of the previous ones, as has been usual in subsequent scientific policies. The weighting of the different lines of research through budget allocation and the allocation of equipment and human resources is the golden rule of techno-scientific rationality, in other words: scientific policies are structurally pluralistic, since they finance in parallel different lines of research, and even opposed. Effective evaluation criteria are evident when analyzing this type of indicators and strategies. This is one of the reasons why the axiology of science, based on indicators and evaluation protocols of the projects, constitutes one of the appropriate ways for the analysis of technoscientific activity.

From that date, many other scientific, technological and industrial contributions were produced. It should not be forgotten that, in addition to designing the bomb and demonstrating its theoretical possibility, it had to be built and tested 128. We will not go into these details, so as not to extend too much in the description of the Manhattan Project. What has been said up to now is enough for our objectives in this section. We are facing one of the great paradigms of the macroscience, with all the specificities that we have attributed to it in section I.4, apart from many others that are specific to the Manhattan Project. Building the pump was a matter of great technological, industrial and financial complexity, but the final technoscientific actions (Hiroshima and Nagasaki) would not have been possible without the strict dedication of great scientists to the project, coming from several disciplines. The plurality of agents needed is one of the most notable aspects of the Project, as well as the total primacy of a military objective, for which enormous financial, human, technological and industrial resources were mobilized. As Hoddeson stresses: “to solve the difficult and complex problem of implosion before the end of the Second World War, it was necessary to develop a new and powerful way of research, in which scientists, engineers, metallurgists and artisans worked closely together, appropriating and others from others’ toolboxes “129. To a greater or lesser degree, this is one of the typical characteristics of macrophysics projects.

From a methodological point of view, pluralism was also very considerable. The success of the Manhattan project can not be attributed to changes in theory (although there were some) or to new scientific methods. On the other hand, the radical transformation experienced by the scientific and technological practice throughout the project is a causal factor of its success, as those who have thoroughly investigated the development of it have underlined. Without the huge funding of the US Government, without the militarization of research, without the collaboration of large industrial companies, some of which had incorporated new methods of production and organization and without the strict discipline to which the scientists and scientists were subjected. the engineers, the atomic bomb could not have been manufactured in such a short period of time. The emergencies derived from the warlike activity were decisive for this first great example of macrophysics to be successful. Subsequently it became a canon of how to act in macro-scientific research. That is why we take it as one of the starting points of the techno-scientific revolution.

The analysis of other examples of macrophysics would lead us to similar conclusions, although, of course, with nuances and significant differences. The same could be said of the properly technophysical projects, such as the large particle accelerators (Brookhaven, CERN, etc.) 130. As we said earlier, a careful study of the development of macrophysics and its transition to technophysics would require much more space. broad and, in addition, the confluence of different types of analysis. The philosophy of science is not enough to study this type of case. In order to thoroughly analyze the changes in the structure of scientific practice, the collaboration of different experts in science and technology studies is required.

As a conclusion, and always as hypothesis to be empirically investigated, we will conclude that technologies and very diverse scientific disciplines intervene in technophysics, but practically always the computer technologies, as well as in the technomathematics and technoastronomy. The calculation of the critical mass of enriched uranium or plutonium needed to blow up an atomic bomb would not have been possible without the help of the computers provided by IBM and the new numerical calculation techniques provided by these machines, as well as the ENIAC in the final phase of the Manhattan project for simulations in fluid dynamics. The same applies to the calculation of projectile trajectories, the movements of particles in large accelerators and in general of nonlinear physical systems. The resolution of this type of problems was the main reason that led von Neumann to get personally involved in the ENIAC and Manhattan projects. The same could be said today of many other branches of physics: meteorology, wind tunnels, aeronautics, etc. But the clearest example is research in small particles, which depends entirely on the construction of large particle accelerators and the information technology essential to process the data. Having one of these technophysical laboratories is a necessary condition to investigate in this field and detect new particles. The same applies to current nanotechnologies, which are a hybrid between physics, molecular biology, engineering and information technology. It is no exaggeration to say that technophysics is the vanguard of research in physics, notwithstanding the fact that there are still theoretical physicists who, based on the technodata, construct concepts and propose laws according to traditional scientific methodology. The technophysics not only generates discoveries, also inventions and new theories. The important thing is that it generates them from a previous research practice that requires a deep hybridization between scientists and technologists, as well as the support of other technoscientific agents that have their own objectives and goals.

(d): Technochemistry.

Since the industrial revolution, chemistry has been closely linked to business activity. Therefore, it is not surprising that the first chemical macroprojects were developed by private companies, specifically the Du Pont Company. In order to diversify the sources from which technoscience comes, in the field of chemistry we will focus on the R & D policy deployed by this company throughout a good part of the 20th century, because it shows very well that the macrochemistry and macro-sciences can also arise thanks to private initiative. As Hounshell points out, the term Big Science usually refers to “scientific projects financed by the Government that involve massive expenditures on large equipment around which large teams of researchers work” 131. However, private companies have developed some macro-scientific projects according to their respective R & D policies. In the case of technoscience, it is the most common, since private investment in R & D exceeds public investment in the US since the 1980s. Therefore, it is convenient to analyze in a certain detail the way in which macro-science emerges in a private company.

The Du Pont Company created its first R & D laboratory in 1902, following the ideas of one of its founders, Pierre S. du Pont, for whom investments in basic research were part of its corporate strategy:

“In our Experimental Laboratory we should try to have at all times some research whose hope of success is very great, although in parallel they may have a high cost for their development, requiring prolonged research, even several years, as well as the use of considerable resources . I raise this policy for two reasons: first, because it will make it possible to have a group of well-trained people whose stable employment is insured. Second, and more important, because in this way the value of the Laboratory will eventually be much greater “132.

This business policy had as a paradigmatic result the invention of nylon in 1940, not only because its commercialization produced enormous benefits to the company, but above all because the organizational model that led to this discovery became canonical for Du Pont, as well as for the Manhattan project and other macroprojects in the 40s and 50s. Du Pont was called to collaborate with the Los Alamos project for this reason, attributing the important responsibility of directing the production of plutonium, which he did with great efficiency in the famous Clinton factory from the outskirts of Chicago. Therefore, we will focus on these two examples of macro-science, of the many that could be found in the Du Pont firm.

In the 30s, Du Pont was a company that intervened in very different businesses: paints, plastics, explosives, chemical products, synthetic ammonia, cellophane, etc. Charles Stine, the head of the central research office, created in 1927 in Wilmington, Delaware, a basic research group, arguing that it could be useful for several production sectors of the company at the same time. One of the scientists he signed was Wallace H. Carothers, a Harvard chemist, whom he put at the head of the polymer research group, with the explicit mandate to do basic research in chemistry. The initial team of Carothers was not very numerous (9 researchers), so we can not talk about polymer mega-science in the 30s. But the unexpected discovery by this group of neoprene, the first synthetic fiber, and especially nylon, a polyamide, greatly reinforced the basic research group. In 1934, the Du Pont R & D Department employed 850 scientists and engineers dedicated to basic and applied research. Bolton, the successor of Stine in the direction of the basic research laboratory, introduced a new organization in the research activity, which over time became the main organizational model of R & D in the company. This organizational change is what turned the small science and applied research into the industry that Du Pont promoted since the beginning of the century into an authentic macro-scientific organization, and with techno-scientific time.

First, the Department of fundamental research began to work closely with two other Departments of the company, oriented to applied research. This led to the link between scientists, engineers and marketing experts. In addition, Bolton created a steering group, which he named the Steering Committee, which brought together the leaders of the various investigative teams along with those responsible for the direction of the investigations. There were two weekly meetings and attendance was mandatory. The function of the Committee was to coordinate the investigation. Meetings were held to review the research carried out by each group, in which researchers or groups presented the results they were obtaining. They also organized the nylon project in parallel, without waiting for each group to have obtained the expected results to start up the other research teams. In summary, a coordinated research model was created, directed and continuously supervised by management, dividing the research into components, starting up all of them and planning the progressive syntheses and convergences between the respective results. The industrial plant for the manufacture of nylon was built when the investigation was still in progress. The same can be said of the studies carried out to launch the synthetic fiber to the market, which indirectly influenced the orientation that had to be given to the research activity. In total, the company spent more than 15 million dollars on the nylon project, an unusual amount for the time, because it exceeded that of some government departments. The commercial success of the launch, aimed exclusively at female bras, was enormous. From the 40s, Du Pont oriented its production towards other garments and objects, but the important thing was that it attributed the success of the nylon project to the close collaboration between scientists, engineers and marketing experts, as well as the management model of I + D that Bolton had designed.

The success of nylon contributed to the prestige of the company throughout the US and its R & D management model became canonical. In 1942, Arthur Compton contacted Du Pont to commission the design, construction and commissioning of a plutonium production plant, provided that the deadlines for this were minimal. Unlike uranium, plutonium could be produced in large quantities, which is why the designers of the Manhattan project always opted for two possible routes for the construction of atomic bombs, one for uranium and the other for plutonium. The efficiency of Du Pomt in fulfilling the order received was decisive for the development of the Manhattan project, as we saw above. The company inspired confidence for its long tradition in R & D, but above all for the organizational model it had put into operation for the nylon project.

It should be said that at this moment is when the company Du Pont is really involved in a macro-scientific project. The nylon project was a prelude to that. At the beginning it was a classic industrial research project. But the incorporation of basic scientists and the new organizational model transformed it into one of the great forerunners of privately financed technoscience. We can conclude, therefore, that the company Du Pont provided one of the distinctive features of technoscience, notwithstanding that its organizational model was modified and corrected in subsequent decades. The scientists who worked on it lost the traditional autonomy that characterizes academic science. The priorities, the concrete objectives and the deadlines to achieve them were given by the Committee that directed the investigation. Some of the members of this Committee were relevant scientists, but as R & D managers they assumed other values and priorities, apart from purely epistemic ones. This transformation is a constant in the passage from science to technoscience. In this case the strategies of the company prevailed, in others those of NASA or those of military institutions. The technoscience always implies a mixture between specialists with diverse formations and interests, as well as a pre-established scientific policy and new models of organization of the research activity.

(e): Tecnomedicine.

The relationships between medicine and biology have always been very close. In addition, a good part of the research in these two sciences has been based on the contributions of physics, chemistry, pharmacology, etc. In this section we will make brief allusions to some of the macro-scientific developments in medicine. Other aspects will be considered when we talk about technobiology.

The emergence of macrophysics at the time of the Second World War strongly influenced medicine, both in scientific and technological aspects. The development of nuclear physics induced the creation of physiological markers of radioactive phosphorus, which began to develop at the Radiation Laboratory of Lawrence in Berkeley. In general, radioisotopes supposed an important technological improvement in medicine, contributing to the appearance of a new discipline, nuclear (or atomic) medicine. In 1936 the first clinical uses of these new techniques were produced.

However, macromedicine itself emerged after the war as a derivation of the Manhattan Project. The Medical Division of this project put into operation several laboratories in the period 1942-45 (Chicago, Rochester, Berkeley, Columbia and Washington) in order to study the effects produced by the exposure to radiation emitted by radioactive materials, as well as the toxicity of the chemical materials that were required to process the uranium. After the war, the members of that Division, with the physicist Warren at the head, were clear that this line of investigation should continue. They also thought that nuclear medicine could bring an authentic revolution in biology and medicine. 133. Penicillin (1940) was the medical breakthrough of the Second World War, but the investigation of nuclear energy opened a wide and novel research field, that attracted physicists, chemists, doctors and biologists, with the indispensable collaboration of engineers and technicians. In 1948, Stanford Warren, who was Nobel Laureate in Medicine, led the development of the new specialty, occupying key positions in the various institutions that were created.

The Atomic Energy Commission took over from the Manhattan Project and maintained its interest in medicine. Warren advocated that all the discoveries that had occurred during the war in the field of medicine and biology cease to be secret. It also fostered the creation of research laboratories of the Faculties of Medicine, the connection with hospitals and the creation of a Radiobiology Society that will bring together the emerging scientific community. The Atomic Energy Commission (AEC) adopted the Warren plan and the Universities that had collaborated in the Medical Division of the Manhattan Project continued to receive funding similar to that of the war period, with other academic and hospital institutions joining the nascent radiobiology. This was one of the ways in which macromedicine and macrobiology emerged, directly influenced by the Manhattan project. The University of California at Los Angeles, for example, signed a contract (GEN-12) very important with the AEC in 1947, for an amount of $ 250,000 per year. This allowed boosting biophysics, radiology and nuclear medicine. Subsequently an Institute to investigate cancer was created. Overall, Warren was the promoter of a large multidisciplinary project and had the success of connecting it with teaching (Medical School) and with the clinic (Wadsworth Hospital, Birmingham Veterans Hospital), which allowed to train specialists in the new subjects and apply the new knowledge immediately. The same happened at Berkeley (Donner Foundation, specializing in cancer research), Rochester and other American universities.

According to the Bush Report, the new structuring of scientific activity came fully into medicine, both in the context of research and in the context of application and education. Obviously, this only happened at some universities, not at all. Emerging macromedicine coexisted with classical medicine, although not without conflicts when it came to apportioning the budgets of the National Health Institute. Overall, it can be said that macromedicine emerged in the US immediately after the Second World War and as an extension of the Manhattan project in times of peace. We thus verified the enormous importance that this project had when it came to restructuring the North American system of science and technology. Obviously, the industry collaborated actively in the task, manufacturing the new precise instruments. The interdisciplinarity of research is one of the aspects that stand out most in emerging macromedicine from 1946-47.

Another very important initiative was the Isotope Distribution Program, designed by the National Science Foundation and executed by the AEC. It was directed by Paul Aebersold for twenty years, moving the laboratories from Los Alamos to Oak Ridge, with the status of National Laboratory. The creation of this type of national facilities has characterized the scientific policy of the USA during the 20th century and, as we have already seen, constitutes one of the distinctive features of macro-science. In the case of large laboratories, very expensive in their construction and maintenance, the only way to make them profitable was to make them available to numerous universities and research centers. This requires sound management and, among other consequences, forces cooperation and coordination between teams that are scientifically competitive. The Oak Ridge Institute of Nuclear Studies was used by scientists from various disciplines, including biologists and physicians. The separation between the scientific communities was broken, since they collaborated in fact in multidisciplinary teams financed by the Government and its specific Agencies. This Institute is a good example of a macro-scientific industry, in this public case, whose functioning and organization is completely different from that of academic communities and laboratories. One of its objectives was to stimulate the industrial and medical uses of nuclear energy. 134. The aim was to disseminate the knowledge that had been obtained during the war and that which was still being obtained by basic and applied research laboratories, but not only through the classrooms and scientific publications, too, but transferring this knowledge to industries and hospitals, that is, in what we call the application context. The end of the war meant the return to normal academic activity in the US, but also the emergence of a new model of scientific practice, which had specific precedents before the war, but which now arose as a result of a pre-engineered scientific policy and systematic Although the autonomy of these macro-scientific industries was very large, behind them was the Federal Government, insofar as it had been involved in the task of promoting research and development.

Many other great examples of macromedicine could be mentioned, such as the war against cancer that the Nixon administration promoted in the 1960s, but the brief mentions that we have made can be enough to outline the main lines of change, which also occurred in the field of Medicine. Of course, new disciplines appeared and important scientific advances were also made. But in this work we are concerned only with the transformation of scientific practice, and this also happened in medicine. The first large companies specializing in radioisotopes (Tracerlab in Boston, Abbott Laboratories in North Chicago) were created in the late 1940s. The goal of scientific policy was not only to create knowledge, but also to generate industries and immediately apply scientific and technological advances in the improvement of the sanitary level of the country. If we analyzed only the progress in knowledge, we would understand only part of the objectives of post-war scientific policy. The Oak Ridge Institute manufactured radioisotopes (scientific factory) and then distributed them freely to relevant scientific, industrial and hospital agents at a rate of $ 300,000 per year (1949). It also trained experts in radioisotopes, contributing to the dissemination of knowledge and the creation of a community of professionals, who were then to be inserted in industries, hospitals and research centers throughout the country. Subsequently, the acquisition of radioisotopes was subsidized, as the industrial sector grew. The Oak Ridge Center functioned as a knowledge factory, but also as an engine in the health macro science sector, within the North American S & T system.

The Atomic Medicine Program, which had funds of 500,000 dollars per year, was decisive for the emergence of industrialized macromedicine. The 12 units of radioisotopes of 1949 became 33 in 1953. A medium laboratory had a considerable area (between 1200 and 3000 square feet) and a good part of them were in hospitals. The important thing is that these laboratories were coordinated with each other through Oak Ridge, since this Center was the matrix of all of them. Medical laboratories were transformed throughout the country, according to a new laboratory model designed by experts in scientific policy, built by industrialists and used by scientists and technicians.

The privatization of laboratories and hospitals, together with computerization and other factors, subsequently transformed macromedicine, converting it into a technomedicine. In this work we will not deal with this new phase, leaving it open to further investigations.

(f): Technobiology.

When we talked about technomedicine, we saw that the first developments of macrobiology arose as a consequence of the Manhattan project. However, the great biological macroproject is the Human Genome, which was launched in the 90s. It is a properly techno-scientific project, in the sense that we give to this term, and therefore we will consider it as the canon of the technobiology. Before commenting, however, it is worth mentioning the transformations experienced by biology in the 50s, and specifically genetics. At that time, technobiology began, although not with the scale it acquired at the end of the 20th century.

The change in biology does not come from macrophysics, but from what we have called technomatemática. During the war, the Office of Scientific Research and Development (OSRD) had funded projects on computational issues of interest to ballistics. Norbert Wiener collaborated on these projects. From this arose his first proposals on servomechanisms and physiological homeostasis, made jointly with Bigelow and Rosenbleuth. In the final stage of the war, Wiener and von Neumann promoted studies on digital automatic control, which later became the origin of cybernetics 135. Both worked in biology as of 1945, starting from a computational model: machines that self-reproduce. The biomedical community with which von Neumann came into contact encouraged him to develop these models as a heuristic tool to investigate genetic actions. In 1948, Wiener published his famous book Cybernetics, or Control and Communication in the Animal and Machine, in which automatons and biological organisms were compared. Wiener agreed with von Neumann in thinking that amino acids make up protein chains through combinatorial procedures and applied mathematical models to the reproduction of genes and viruses. Both introduced a new paradigm in genetics, in the Kuhnian sense of the term.

That same year, Claude Shannon published an important article on his mathematical theory of communication and the following year he disseminated those ideas in collaboration with Warren Weaver, director of the Rockefeller’s Foundation Natural Science Division and the molecular biology program of the Foundation. Shannon was involved in questions of cryptanalysis and code theory, and introduced concepts such as redundancy and binary coding, always in the field of communication between machines. As a result, cryptology and electronic computers (specifically MANIAC, continuation of von Neumann’s EDVAC) began to be used to analyze genetic codes. Altogether, the impact of the ideas of Wiener, von Neumann and Shannon was enormous, to the point that genes began to be considered as biological machines that communicate with each other using encrypted codes, and not only as biochemical organisms. The notion of genetic code was widely accepted and used, as well as the computational methods to investigate and decipher it. Henry Quastler took on the task of rethinking biology as an information science. His writings were highly commented, so that when Quastler organized a major symposium on Information Theory in Biology at the Control Systems Laboratory at Brookhaven (1952), the new paradigm found an emerging scientific community to develop it. Quastler proposed estimates of the amount of information that exists in a human organism (5×1025) and from this he calculated that the genetic description of a human being could contain 5×1021 pages of information. What he called the genome catalog would have about a million bits.

In short, just before Watson and Crick published in 1953 his famous article on the double helix of DNA, a new paradigm had been installed in the field of biology, and more specifically in genetics. The discovery of the double helix by Watson and Crick was typically scientific, based on observing photographs of which Watson inferred the existence of helical structures in the genes. However, prior to this, a new paradigm had been established in genetics, which required the use of powerful computing tools when investigating, given the magnitude of the magnitudes of information considered. In addition, the new paradigm transferred to biology a series of concepts from computing sciences and the theory of artificial systems. The current genetics is not only based on the double helix, but also on the notion of genetic code and derived concepts. Therefore, we affirm that, unlike Mendelian genetics, the genetics of the second half of the 20th century had a strong techno-scientific component, which was further reinforced with the introduction of recombinant DNA techniques and, above all, with the Genome project Human.

In the 50s there was an authentic proliferation of combinatorial models, all proposed in order to decipher the genetic code, a notion that by then had been fully consolidated among researchers. Crick himself, modifying a proposal by George Gamow (diamond code), proposed in 1956 the famous code without commas, which subsequently proved inadequate. Teller suggested a sequential code. And other scientists (biologists, physicists, mathematicians, engineers, etc.) proposed other models. The central problem of genetics at that time was to investigate the transfer of information from nucleic acids to proteins, always starting from the hypothesis of coding and resorting to the most powerful computers of the time for empirical research, given the magnitude of bits that were handled. For its part, Watson began to talk about inter-bacterial information, for example, expanding the new paradigm to other fields of biology, apart from genes. The new infobiological (or info-genetic) paradigm advanced rapidly in the 1950s, attracting the best researchers, always in collaboration with mathematicians, engineers and computer scientists. Do not forget that in his seminal article of 1953, Watson and Crick already said clearly that:

“It follows that in a long molecule many permutations are possible and therefore it would seem that precisely the sequence of bases is the code that translates the genetic information” 136.

This stage supposed the emergence of computational biology, one of the most important technobiology modalities. An in-depth study of it would provide data of great interest, but with what has been said so far is enough as a first introduction. Of course, parallel biochemical investigations continued. But the infobiologists, so to speak, had constituted a new community, which can be described as techno-scientific, according to the distinctive features that we have pointed out in the previous sections. Some of these investigations were supported by military institutions, as well as by companies.

The Human Genome Project is a continuation of this line of research, although in the midst there were relevant contributions, to which we will not refer, for the sake of brevity 137. By the end of 1966 the entire genetic code had been deciphered and could be closed the first stage of informational or computational genetics.

The origin of the Human Genome Project (HGP) has to do with the relative success of the war against cancer program promoted by the Nixon administration in the 1940s. In 1986, the Italian Nobel Prize winner Renato Dulbecco published an article in Nature stating that there was to change strategy, promoting a large-scale research program instead of the gradual approaches that were being made. That is to say, he proposed a macroprogram of genetic research, which, as he said:

“In importance it would be comparable to the conquest of space and should be undertaken with the same mentality. And it would be even better if it were an international company, because the sequence of human DNA is the reality of our species and everything that happens in the world depends on its sequence “138.

Independently of the genetic determinism that underlies this proposal, and which constitutes one of the main conflicting points of the HGP, Delbecco’s proposal was well received. It transferred some postulates of the macroscience to the genetics. Not in vain the Genome Project is often called “the Manhattan Project of Biology”. On the other hand, the North American Department of Energy revolved at that time to a similar idea, through the Director of the Office of Health and Environmental Research of said Department (DOE, as of now). Indeed, Charles de Lisi had organized a small symposium on the subject in March 1986, in which the idea was accepted, but it was questioned whether the DOE was the appropriate agency to promote such a project. The National Institutes of Health (NIH) was an obvious candidate to do so. There were also private companies that caressed similar ideas, such as the Genoma Corporation, although it had to renounce the project because it did not find sufficient capital. Private financing was not large enough to undertake macroprojects, although smaller techno-scientific projects. Incidentally, we note with this an important difference between the simultaneity of discoveries in modern science and in technoscience. In the latter case, the most frequent is that two or more techno-scientific companies (public or private) simultaneously imagine or design alternative research projects on the same subject, not that a fact is discovered simultaneously in a laboratory. In technoscience companies compete with each other and the key point is to start the projects at the right time, in addition to finding the right financing for it. The design of the projects is of fundamental importance when it comes to obtaining acceptance and support. Hence the importance of techno-scientific pre-actions, that is, the design and planning of what is intended to be carried out. It is assumed that, once a project like the HGP has been started, the scientific facts will emerge in addition.

Since within the Government Agencies there were at least two willing to undertake the HGP, the DOE and the NIH, the National Science Foundation mediated, creating a special Commission to study and design a possible Genome Project, as well as the institutions that could take it to cape. This Commission advised that it be an international project, although led by the United States. Instead of sequencing the DNA, which was extremely expensive, at least until important technological advances were made, the Commission proposed to first map the human genome, as well as characterize the genomes of other organisms (mouse, fruit fly and some yeasts and bacteria). At the same time, research had to be financed to improve the technologies that would allow for cheaper sequencing 139. On the other hand, there was no pronouncement on the Agency that could be responsible for the project, the DOE or the NIH. Congress approved the initiative in principle, so the DOE and the NIH went on to budget it. Two government agencies competed before Congress to achieve the concession of a macroproject for research, in the same way that university teams and research companies compete with each other in public calls for scientific policy. The DOE’s first budget (1988) came to 12 million dollars. But the Director of the NIH, James Wyngaarden, considered that some 50 million were required so that the objectives could be truly fulfilled. This gave more reliability to the second project, after the corresponding evaluation. The final endowment of the project was 3,000 million dollars for several years. The subsequent problem was to find a person with sufficient prestige and political capacity to manage a project of such magnitude. In the end, James Watson was appointed Director of the HGP, a position he held from 1988 to 1992, date on which he resigned, due to strong dissensions with the new Director of the NIH.

This appointment is of great interest to us, for several reasons. In the first place, because it confirms the idea that prestigious scientists are essential for techno-scientific companies when it comes to directing macro-projects. However, these scientists are not asked to contribute theories or to investigate in laboratories. What they demand is that they manage the project, design strategies and, above all, have good relations with various scientific-technological communities and with experts in scientific policy. If, in addition, your image inspires confidence in the public and potential investors, so much the better. Scientific merits are necessary, but they are not enough to be placed in this new scenario of technoscience: the management of a macro research project. This type of selection process is based on several value systems and manifests the effective values of technoscience.

Secondly, one of Watson’s first decisions was that 5% of the HGP would be dedicated to investigating the ethical, legal and social repercussions of the new project. As we will see in chapter 5, this decision implies the explicit recognition that social, legal and moral values are also relevant in macro-scientific research, at least to study its consequences, something that would have been unthinkable at the time of the Second World War. , when values and military objectives prevailed over any others, including economic ones. Thus arose the ELSI subprogram (Ethical, Legal and Social Implications), which has had great importance as a model to follow in scientific policy. Even if peripherally (5%), legal, moral and social issues began to have a certain presence in the design of the macroprojects.

Third, a new research center was created to develop the program: the National Center for Human Genome Research, following the Bush model of scientific policy, but in this case with Watson at the head. There are no great techno-scientific actions without new institutional or business agents, which are inserted into the national systems of science and technology. In this case, the project went beyond national borders, since important centers in the United Kingdom, France, Germany and Japan decided to collaborate with NCHGR, providing funding, human resources and equipment, among other things. The coordination of the project was international, which made telematic networks indispensable to interconnect the various participants in the techno-scientific consortium. The New Center was designed as a laboratory-network, in the sense that we have attributed to this term in section II.2.

Fourth, a strong conflict of values between the Scientific Director of the Project, Watson, and the financial and political management (represented by Bernardine Healy, appointed Director of the NIH by George Bush in April 1991), eventually forced the resignation of Watson:

“Healy had strongly supported the controversial decision of the NIH to apply for the patent of the hundreds of gene fragments identified by its scientist Craig Venter, if only for the patent office to be defined on the possibility of patenting genes without any known function. Watson censored Venter’s investigation and was very outraged by Healy’s decision to go ahead with the patent application. To make matters worse, Healy asked Venter to advise her on the future of human genome research at the NIH while telling Watson to refrain from expressing more criticism in public “140.

Already in this first skirmish of the PGH we can verify that it is not enough to be a great scientist to be a good scientific manager. The appropriation of knowledge, in this genetic case, is part of the structure of technoscience, unlike science, in which knowledge is a common good that is made public, with exceptions. Even working for the NIH, Venter represented the technoscientific entrepreneur who later came to be when founding Genome Celerics and defended business values alongside traditional values of science, such as knowledge advertising. The map of the genome, and especially its subsequent sequencing, is not only an epistemic good. In the era of technobiology, first of all it is an economic good, or to put it more clearly, a new form of capital. The Reagan administration had already decided in the previous decade that the government should be replaced by the private initiative to lead scientific research, whenever possible. It is not surprising that the Bush administration retakes that policy, despite the enormous national and international prestige of Watson.

Watson was succeeded by Francis Collins, although Venter was increasing his prestige. Starting in 1986, he introduced the automatic sequencing method, using one of the few then existing sequencing machines, which allowed the analysis of hundreds of genes at the same time, while the other researchers studied them one by one. a decisive step towards the conversion of genetics into technogenetics. As of that date, all the investigations of Venter had great computer equipment. In 1991, Venter and Adams conceived a new method of sequence, the EST (expressed sequence tag), which opened the controversy of patents in the PGH. Craig Venter culminated his career in 1998, when he informed Collins, Watson’s successor, that he was going to create a new company that would sequence the genome before 2005, the date initially planned for the PGH project. For this, I was going to resort to a new sequencing technique, to hundreds of sequencing machines and to one of the most powerful supercomputers. This purpose was publicized in the press, in order to attract funding. The creation of Celera Genomics forced PGH to increase its funds in order to compete with Venter in the techno-scientific career. For two years, the technogenetic contest took place in laboratories, financial offices and the media. The mediation of President Clinton put an end to this “techno-scientific controversy”, with both teams reaching a pact in June 2000. In the end, the public and private teams were able to announce 2002 the culmination of the work.

However, Celera Genomics had introduced important novelties in the research practice, which were quickly imitated by other technobiology companies. Apart from those already mentioned (patents, mass use of computers, communication campaigns in the mass media, etc.), there is a derivation that we are interested in highlighting, because it illustrates very well the link between technoscience and the economy of information and knowledge .

In 1992, Reid Adler, Director of the Office of Technology Transfer of the NIH, had attempted to patent the first 2,500 partial gene sequences obtained with the EST method. After a great controversy around the world, in which Vice President Al Gore intervened (apart from John Watson, of course), the US Patent Office rejected the request, largely because it tried to patent not only the partial sequences, but also the underlying genes, many of which were still to be identified. After a second attempt with 4448 EST, the NIH declined to request more patents. By then, Venter had stopped working for the NIH, because a request from him for a $ 10 million research project had been rejected. He went on to direct the Institute for Genomic Research (TIGR), a non-profit organization funded with $ 70 million by a sponsor, Wallace Steinberg. The Institute was equipped with 30 ABI 373A automatic sequencers, 17 ABI Catalyst stations and a relational database installed on a high-powered Sun SPARC Center 2000 computer. The immediate objective was to multiply the EST production rate by 10, which is why the Institute became a great techno-scientific factory, with the peculiarity that it only produced sequences, that is, information. In the long term, the scientific goal was to investigate evolution by comparing the sequences of the different species. It was, therefore, a strictly infogenetic macroproject, where all the instruments were information and communication technologies. Therefore, we will consider the TIGR as the main canon of technobiological enterprise of the late twentieth century.

But the news did not end there. To recover his investment, Steinberg created a company associated with the Institute, Human Genome Sciences (HGS), and gave 10% of the shares to Venter, for having co-founded it. The subsequent success of TIGR among scientists, and the parallel business success of HGS, made Venter one of the first scientists to become billionaires. The technogenetic research could not only be profitable for the entrepreneurs who financed it, but also for the researchers themselves.

Beginning in 1993, HGS became a pharmaceutical company. Its strategy was to sell the access to the EST database to companies in the sector. In May 1993, a British company (SmithKline-Beecham) paid $ 125 million for 7% of the shares of HGS along with the exclusive right to market the ETS. The scientific knowledge of the TIGR database had become pure and hard capital, which began to be highly profitable for Steinberg and Venter. The latter and the President of HGS, Haseltine, came to occupy the cover of Business Week magazine: a way of doing business with scientific knowledge had emerged. The relational database of the TIGR became a real mine of knowledge, which was generated by Venter and his team of scientists with the help of new computer equipment, increasingly powerful. The techno-scientific revolution in Biology thus found one of its most outstanding examples, in the Kuhnian sense of the term. The scientific practice was radically transformed, because research was superimposed on a novel and profitable business strategy.

The scientists received this change with significant samples of rejection, but similar companies began to proliferate around the world and there was no shortage of researchers working on them. Venter himself ended up founding his own company, as we saw. In any case, it can be said that the most radical transformation of the structure of scientific practice in biology occurred in the 90s in the TIGR, being Craig Venter and his partners who led that techno-scientific revolution in biology.

There would be many more questions to discuss, but we have already expanded sufficiently on the PGH and its subsequent privatization as HGS, and subsequently as Genome Celerics.

To summarize this first analysis on the emergence of technobiology, we will say that informatics and the disciplines that emerged from computing sciences have played a very important role in the transformation of biology, and in particular of genetics. The sequencing of genes is primarily a technological operation, which requires considerable means and technical skills. The data obtained (the map of the human genome, for example) are strictly computerized, so that they can only be represented with the help of powerful computers. The enterpriseization of the research activity is very common in genetics. On the other hand, we have verified that the Genome Project ended up generating authentic knowledge banks, which produced considerable economic benefits. On the whole, also in the case of biology, it can be said that at the end of the 20th century a technobiology with a strong computer and business imprint emerged. The advances in knowledge that it has raised are undoubted, but it is also evident the profound transformation of the scientific practice that has taken place throughout the second half of the 20th century, and above all in its final decade.

(g): Technogeology.

Observation satellites and computer technologies have profoundly modified the way of making the geological planes of the Earth, the Moon or Mars, completely transforming geological knowledge and practice. Some observation instruments allow the detection of concrete objects or substances several meters deep. The traditional probes were mechanical, the current ones are telematic. Once again, this is a clear example of technoscience.

In this case, too, computer technology plays a basic role, for example, using three-dimensional representation techniques. We will limit ourselves to mentioning how the geologists themselves conceived this technogeological, or infogeological, revolution, as it could also be called: “At present, geologists are participating in a technical revolution that has greatly expanded the possibilities of visualization and scientific interpretation through use of sophisticated techniques of three-dimensional presentations “142. These techniques are essential to simulate geological processes, that is, to represent computer science knowledge. It should be noted that this type of technology has been strongly promoted by oil companies, obviously interested in the advancement of technobiology and technobiology. The research departments of these companies usually use the most powerful computers on the market (CRAY I and II, etc.), so in this case we can also say that technobiology has been widely developed in the last quarter of the 20th century. Even so, experts in the field affirm that “one of the axioms of computer simulation processes is that computers never provide the computing power that would satisfy the needs of geologists” 143. Having large computer equipment is a necessary condition for research in geology and to apply this knowledge to the petroleum industry.

The new information and telecommunication technologies are also used for geological remote sensing and for the simulation of the great cataclysms that occur in the terrestrial globe: volcanoes, earthquakes, tidal waves, etc. The same can be said of marine geology, whose progress is closely linked to new technologies. On the whole, technogeology has developed enormously in recent decades, which does not prevent the existence of classical geology, based on the traditional methods of technoscience. Also in this case it is necessary to distinguish between geology and technogeology, without prejudice to the fact that both have a common juncture, because the second comes from the first. The synthesis between science and technology constitutes, in this case, the most outstanding note. But it is also observed the close connection with the big companies, in particular the oil companies.

(h): Social technosciences.

The application of statistics completely transformed sociology, which became a strictly empirical discipline. The important thing is to emphasize that also in this case, given the complexity of societies, technology is an essential requirement to obtain empirical data, as well as to process them, store them, compare them with each other, etc. Opinion polls are a good example of what we say, as well as the elaboration of censuses. The use of automated optical readers to process the raw data shows again that in the case of sociology, obtaining empirical data would be impossible without recourse to various technological tools. The same applies in the case of the economy, whose researchers resort again and again to computer simulations to model the situation of the economy in the different countries. Nowadays it is impossible to have a representation of the economic state of a country without resorting to the tools that allow the processing of data and the elaboration of simulations to make prognosis on the economic evolution.

The examples could be multiplied, but it is not worth dwelling on. We understand that this brief tour of various sciences (natural and social) sufficiently illustrates the emergence of technoscience and, in many cases, its relevance within each specific discipline. Note that in all these cases the computer plays an important role, notwithstanding that other technologies also intervene. That is why we say that informatics is the formalism of technoscience, to the way in which mathematics was the main formalism of modern science. The science wrote the empirical data, the technoscience the infoescribe. The processing and transmission of these data is also carried out via computer and telematic means, as well as the presentation of the results obtained from them. Scientific visualization techniques, on the other hand, allow converting these data into images and scientific models. The construction of scientific models, usually mathematized, has been one of the distinguishing characteristics of the knowledge of scientific knowledge. From these models hypotheses were issued and empirical contrasts were carried out. In the case of technoscience, this type of model is not enough and it is necessary to resort to computer models, whose management requires specific technological equipment and skills. That is why the techno-scientific research teams have to be composed of scientists and technologists. To carry out these investigations, both types of knowledge are required. It is another reason we argue to talk about technoscience, and not just about science.

As a conclusion of this section, we will say that the test of specific technosciences offers satisfactory results. Although not all science has become technoscience, it can be said that in all sciences the emergence of this new form of science has taken place. The many distinctive features that we have proposed in sections II.1 and II.2 are in principle worth distinguishing science from technoscience. In the rest of this book we will take them as starting points for our inquiry.

Chapter III

The techno-scientific revolutions

III.1: The Kuhnian conception of scientific revolution.

Kuhn’s work has had a great influence, above all in philosophy, history and sociology of scientific knowledge. In this chapter we will start with your proposals, in order to examine them critically in the light of the changes experienced by science in the second half of the 20th century. According to Kuhn, “the essential characteristic of scientific revolutions is their alteration of the knowledge of the intrinsic nature of language itself” 144. The techno-scientific revolutions to which we are going to refer do not fall under that characterization, neither in regard to knowledge, nor to nature, or language. Contrary to Kuhn, we will keep the techno-scientific revolutions:

1.- They do not alter only the knowledge, but above all the scientific and technological practice. Knowledge is one of the results of techno-scientific actions, not the only, or sometimes the most important. On the other hand, there is no techno-scientific knowledge without previous actions, so it is convenient to analyze the actions first. During the twentieth century, the main scientific theories have continued to be accepted. Except in some sciences (cosmology, genetics, etc.), there has been no crisis of the main paradigms. However, another type of transformation has taken place, affecting primarily scientific practice: the emergence of macro-sciences and technosciences. To explain this transformation, traditional epistemology is insufficient, including the Kuhnian epistemology. The techno-scientific revolutions are praxiological, not epistemological or methodological. Although they generate new theories and new scientific disciplines, this is an effect derived from the great transformation in the structure of scientific activity.

2.- The technosciences modify the social world, not only nature. The main thing is the transformation of the world they produce, and in particular of the social world. Scientific knowledge is a means to modify the correlation of forces in a war, to obtain economic benefits in the market, to improve the health of a country, etc. This transformation is achieved by developing (R & D) the results of scientific and technological research through companies, military organizations, political institutions, etc., which are the ones that produce social transformation by basing their actions and strategies on the results of the technoscience The epistemological changes provoked by techno-scientific revolutions are instrumental. If they do not generate technological development and innovation, they are not techno-scientific changes, but only scientific ones. Technoscience does not follow the Baconian program, knowing nature well to be able to master it better, but it is oriented towards transformation, control and in some cases the domination of societies and human beings. Technoscience is a new form of power, which is embodied in the organization of science and technology systems in different countries. Therefore, it is closely linked to political, economic and military power.

3.- The techno-scientific revolutions involve a profound change in the scientific and technological language, but this transformation does not concern the relations of meaning between language and nature, which are what Kuhn worried about. According to him, scientific revolutions “alter the language with which nature is described” 145. It is about what Kuhn had called in many of his writings “change of meaning” and that in the essay What are scientific revolutions? he again characterized as “a change in the way in which words and phrases relate to nature, that is, a change in the way in which their referents are determined” 146.

Later we will indicate more differences between scientific and techno-scientific revolutions. For the moment, we will dwell on the question of language, where our opposition to Kuhn is based on a very important nuance, which should be made clear.

When Kuhn refers to scientific language, think of a referential relationship between words and nature. The problem that occupied him most was that of scientific concepts and their changes in meaning when scientific revolutions occur, as well as the appearance of new concepts. In the case of techno-scientific revolutions, new languages also emerge: the computer languages of each discipline. But the function of these languages is not that of natural languages or that of scientific languages (theoretical terms, observational terms, statements of laws, formulation of explanatory hypotheses, etc.). Although they may refer to things and objects, this is secondary.

First of all, computer languages order actions. A programming language is based on commands for a machine to carry out certain actions when a series of previously fixed conditions are met. Said more intuitively: when we press a computer keyboard, a mouse or a touch screen, we order that a previously programmed machine executes an action that we want to carry out. If the resulting action is not as expected, or we have wrong to operate, or the machine does not work well or is not well scheduled. In techno-scientific actions, mistakes, blunders and mistakes are of paramount importance. These are technical errors that radically affect the results obtained. Therefore, the first thing to check is that the machines work well and that the actions have been well carried out. The correction of the actions is a necessary condition, although not sufficient, of the validity of the results. At a later stage, these results (data, images, models, simulations) must be compared with the world. In this second stage we enter the field of semantics and relations of signification, typical of science. But in the case of technoscience, technical mediation is essential, as well as the correction of actions, both when they are performed and, above all, in their previous design. That is why we are facing a new form of science, technoscience, where the first is the correction, control and verification of technical actions by an expert and then performed by an operator, or sometimes by a machine, when the design involves automatism. Semantic issues are relevant in technoscience, but the design, adaptation and correct execution of actions is a prior and different problem to that studied by Kuhn. To put it in terms of Hacking, first we intervene, then we represent 147. By reducing philosophy to the problem of linguistic and conceptual representations of knowledge we are forgetting what we have done previously to obtain the data we represent.

From the above, important philosophical consequences derive. In the first place, there are no techno-scientific facts without previous actions. The facts are not given by nature, are not offered to our immediate experience, arousing our curiosity. On the contrary, they must be obtained after deploying enormous observation and experimentation devices, which must work well. For example, when physicists use a particle accelerator, they carefully design the experiments they will perform. These experiments are very expensive and therefore have to be projected with care and precision. If, after having carried out a concrete experiment, it is believed to have discovered a new elementary particle, its existence is always inferred from the data offered by the accelerator and the other instruments that implement it. Any error of the devices or operators, however minimal, completely invalidates the experiment. Therefore, techno-scientific research involves continuous controls, repetitions, checks that there were no errors, etc. It is a necessary condition to continue, which does not guarantee success, but whose absence ensures failure. Once the correctness of the design and the execution has been verified, the data obtained by the accelerator become scientific facts, after repeating the experiment and subsequent verification by other operators. From there the classic scientific methodology can be applied, elaborating hypotheses, interpreting the facts, trying to explain them (or even predict them), formulating laws, etc. But those semantic and epistemological questions are empty words if a small error is discovered in some action, or a malfunction of the devices, or some unforeseen factor in the design of the experiment. These prior technical demands raise important philosophical questions, for example the need to have a theory of correct action, not just justified or valid knowledge. The history of science is plagued with false facts, derived from incorrect actions on the part of the experimenters, including the inadequate design of the experiments.

It is also necessary to compare the actions planned and those actually carried out, to see the degree of adequacy between them. In this case we are facing a problem of correpondence and adaptation between actions, which has nothing to do with the truth as an adaptation of the classical philosophers, but with the problem of intercorrespondence between actions independently of the operator that carries them out. When researching scientifically, different operators repeat the same actions over and over again, sometimes with different devices, being able to obtain slightly different results among them, as is frequent. All these problems are praxiological and, of course, prior to the epistemological problems that later, because technoscience is a form of science, are also aroused. We will say therefore that the notion of truth as correspondence, typical of modern science, is subordinated to the previous correction of actions. We will see later that, in Kuhnian terms, the most serious problem of technoscience consists in the incommensurability between the practices of some operators and others, especially if this incompatibility is produced by machines built by rival techno-scientific companies. In such cases, the first problem is the reliability of the instruments. Some of these technical antinomies already arose in modern science 148, but with the emergence of technoscience they have become pre-solving issues before addressing semantic problems. The technological systems that support scientific research today are so complex that the control of actions and instruments is absolutely essential if we want to accept a certain result as a scientific fact.

In the techno-scientific revolutions there is a radical change in language. Infolanguages or computer languages are one of the distinctive features of technosciences. We operate with computers and other techno-scientific devices producing signal changes (data, images, sounds, etc.). This is where computer languages intervene, to mention only the canonical techno-scientific language. The same happens when it is not the human being that acts, but the changes of state in the systems studied are detected by the machines (detectors, sensors, robots, search engines, automatic translators, space probes, satellites, etc.), causing automatically the actions of the devices. Then, and as an effect of these actions, we will have images or data of various objects (natural, social, artificial) in the various screens and data records. We will be in a referential or meaningful relationship again. But, when this happens, we are no longer using the info-language. We use it when pressing the key, clicking with the mouse or operating the remote control. Before we get to use natural or scientific languages, we have already carried out technological actions based on programming languages. Technolanguages, to put it generically, are an indispensable requirement for technoscientific actions to take place. Even the natural and scientific languages themselves (descriptive, referential, significant, etc.) are transformed by the influence of technosciences, becoming technolanguages. On the other hand, new techno-languages emerge, unknown before the techno-scientific revolution: the TEX of mathematicians, scientific visualization and genetic info-languages are good examples, as we saw in section II.3. The latter are codes and the important thing is the syntax, not the semantics.

In short, and not to dwell too much on this point, the techno-scientific revolutions involve a very important change of language, and in this we agree with Kuhn. But technolanguages are not referential and do not refer to nature, at least in the first instance. The references of the computer languages are not natural objects, but info-objects. The data and the hypothesis are contrasted in this new semiotic space by means of computer simulations, modification of parameters, etc. The Kuhnian characterization of scientific revolutions is insufficient for technoscientists, because computer technolanguages are of a very different nature from classical scientific languages.

III.2: The scientific paradigms, according to Kuhn.

Recall briefly Kuhn’s main proposals on scientific revolutions. The most relevant philosophers of science of the mid-twentieth century (Carnap, Popper, Hempel, etc.) had focused their reflections on scientific theories, which were considered as the basic units for the philosophical and historical analysis of the sciences. Toulmin and Hanson raised the first criticisms of this “teoreticist” model, but it was Kuhn who managed to put it radically in question. He proposed the notion of paradigm to designate that common framework that brings together and agrees with scientists and that is much broader than theories, understood as sets of statements. As Pérez Ransanz has indicated, Kuhn uses that term in two differentiated senses:

“1) Paradigm as an example of a successful (and surprising) solution to certain types of problems, which is recognized by the entire relevant community, 

and 

2) a paradigm as a set of commitments shared by a community of specialists” 149.

This general proposal, as well as its subsequent concretions (distinction between normal science and revolutionary science, anomalies, crisis of a paradigm, scientific revolution, etc.), were exposed in the book Structure of scientific revolutions, which was published in 1962 150, and then nuanced in the Postscript of 1969 and in his Second Thoughts on Paradigms 151. In this review, Kuhn started from a sociological criterion for the identification of paradigms: “a paradigm is what the members of a scientific community, and only they , they share “152. Next, they asked about these shared commitments and proposed a new expression to refer to paradigms as a set of shared commitments: disciplinary matrices. Scientists not only share theories, but rather more broadly, the disciplinary matrices, which have at least four components: symbolic generalizations, models, values and exemplars. In any case, the different meanings of the Kuhnian notion of paradigm are always linked to the existence of scientific communities.

In contrast, technosciences are not made by scientific communities, but by more complex entities, techno-scientific companies. From a theoretical point of view, the members of these companies share far fewer things than the scientific communities. In particular, they do not share the same languages, the same values or the same objectives, which does not prevent them from collaborating in the same research company. In some cases they do not even share scientific knowledge, except very briefly: scientific and technological knowledge is something instrumental for some relevant members of techno-scientific companies. For example, the director of an R & D company can first of all have a managerial or company director training, provided that he has a good scientific and technological adviser at his side. The same can be said of the experts in scientific policy, the Directors of government agencies or the military advisers specialized in R & D. These people are interested in scientific knowledge, but not as an end in itself, but as a means to better achieve their own ends. In some occasions this type of techno-scientific agencies are directed by scientists or engineers with high knowledge in the matter, in others it is enough with a very shallow knowledge of the theories and knowledge that allow research and innovation. There have been no lack of humanities experts who have effectively assumed the leadership of important techno-scientific agencies. Therefore, in the techno-scientific companies, a shared knowledge is not required, much less the acceptance of a certain epistemological paradigm. Even opposite paradigms can be used, in order to prove which of the two offers better results from the point of view of innovation. In fact, in order to carry out a macro-research project, it is not uncommon to finance research teams that work in parallel from different theoretical and methodological perspectives. The important thing is the achievement of the objectives of the project, not the epistemic beliefs of the researchers. A director of a research macro project can have groups whose hypotheses, procedures and working methods are very different, and even incompatible. In fact, it is often the case, as we saw in the case of the Manhattan project. The techno-scientific companies put the different teams of scientists and engineers to compete with each other and what counts is the achievement of the intended objectives, not the greater or lesser likelihood of the theoretical hypotheses of departure. The scientific paradigms are contrasted in practice, depending on the results obtained. Whoever decides the rivalry is not the scientific community, but the techno-scientific agent (military, business, political) that has commissioned and contracted the realization of these investigations with two teams that compete with each other. The same can be said in the case of R & D companies. The managers of these companies are interested in the knowledge that generates development and innovation. The plausibility of the starting theories does not concern them at all, as long as they serve to generate new products that are competitive in the market.

The notion of the scientific community, as conceived by Merton and developed by Kuhn and others, is insufficient to analyze technoscience and to identify the possible “technoscientific paradigms”. All this in the assumption that the term “paradigm” is adequate to talk about technoscience, which remains to be seen. For the moment, we will talk about technoscientific companies that instrumentally use one or other paradigms (or theories) in order to obtain valuable results. In technoscience we are dealing with technical actions, as these were defined in the first chapter. If a basic research laboratory is inserted into a techno-scientific enterprise, even its investigations become technical actions, because they are part of a more complex system in which the scientific theories and hypotheses themselves have a purely instrumental function. A scientist can make very important findings from the scientific point of view, but if those achievements do not contribute to the development of the techno-scientific project in which he is inserted, he will be cornered, and ultimately excluded from said project. He will remain a scientist, but he will not have become a techno-scientist. To be, it is necessary to subordinate the epistemic interests to the general objectives of the project. The history of technoscience is full of examples where the discomfort of scientists in the face of the new situation is manifested, for example when priority is given to obtaining industrial patents as a result of research. Those scientists who assume the plurality of technoscience values, on the other hand, become true technoscientific entrepreneurs, as we saw in the case of Craig Venter.

On the other hand, for a techno-scientific company to develop its activities well, it is necessary to clarify which is its most appropriate organization, assigning tasks, responsibilities and functions. A scientist or an engineer who works as a researcher in a techno-scientific company may completely ignore the ultimate meaning of their actions, which was not the case in classical laboratories. The “techno-scientific” paradigms, if any, have to be very different from the Kuhnian paradigms, because, above the scientific and engineering communities, a new modality of techno-scientific agent has emerged, the public or private company of I + D + i, whose actions make sense within the framework of a network of techno-scientific companies. A public techno-scientific company (for example, an Agency or a National Laboratory – or multinational, such as CERN) differs radically from a private techno-scientific company because of its objectives, sources of funding, management procedures, legal constraints and criteria for evaluating the results that derive from their activity. Then they will compete with each other, for example in the Genome Project, but that competence not only concerns knowledge, but above all, patents, applications, implementation in the market, publicity of results, etc. In particular, techno-scientific companies compete with each other when it comes to integrating the best scientists and engineers into their templates. The competition between paradigms acquires a completely different meaning in the case of technosciences.

III.3: Components of the paradigms.

Let’s go back to Kuhn, analyzing the various components of his paradigms. Symbolic generalizations are the formal components of the paradigms: sometimes they are presented as mathematical formulas (f = m.a, I = V / R) and sometimes they are expressed by words: “the action is equal to the reaction”, for example. According to Kuhn, “the power of science, in general, seems to increase more often than not with the number of symbolic generalizations that its practitioners have at their disposal” 153. They usually express laws of nature, but not only that: they also work “As definitions of some symbols they enumerate … laws are often correctable gradually, but definitions, being tautologies, are not.” 154. Therefore, paradigm shifts usually imply the redefinition of basic concepts: “I suspect that all revolutions involve, among other things, the abandonment of generalizations whose force was, until then, that of tautologies “155.

The second component is the models, which: “provide the group with preferred analogies or, when deeply held, with an ontology. On the one hand, they are heuristic: the electrical circuit can be considered, profitably, as a hydrodynamic system in a stable state, or the behavior of a gas like that of a collection of microscopic billiard balls in random movement. On the other hand, they are the objects of metaphysical commitment: the heat of the body is the kinetic energy of its component particles, or, more obviously metaphysical, all perceptible phenomena are due to the movement and the interaction of qualitatively neutral atoms, in a vacuum ” 156

The third component is the values, understanding as such what we call epistemic values, among which Kuhn explicitly pointed out precision, coherence, amplitude, simplicity and fertility, as well as utility, although this as an additional or external value To science. These values “are usually shared among different communities more broadly than symbolic generalizations or models. And they contribute much to giving a sense of community to natural scientists as a whole “157. Therefore, this axiological component is transdisciplinary, because those values are not only shared by each scientific community, but by all of them, or at least by all those who are dedicated to the natural sciences. This qualification is important, since it shows that the values of science are transversal to their different disciplines, as also happens in the case of technosciences. Although in other places we have already commented extensively on Kuhn’s thesis about the values of science, 158 we will pause for a moment in his conception of these shared values, postponing the analysis of the fourth component of the disciplinary matrices, the exemplars, which “are solutions of concrete problems accepted by the group as paradigmatic in the usual sense of the term “159.

Kuhn maintained that those values shared by natural scientists “work at any time”, although “their particular importance arises when members of a particular community must identify crises or, later, choose between incompatible paths in which they practice their discipline” 160. That is, values emerge explicitly when paradigms enter into crisis, as well as in scientific revolutions. In the times of normal science no questions of values arise, and it may even seem that science is value-free, as many positivist philosophers argued. According to Kuhn, this is not the case. Science has its own values, then called epistemic (Putnam) or cognitive (Laudan). These values are transdisciplinary and play a very important role precisely in times of crisis and scientific revolution. Because they are transparadigmatic, the values of science will be one of the criteria that scientists will use to assume (or not) that a paradigm has entered into crisis (for example, because it has ceased to be fruitful, versus another less precise and rigorous but more fertile) or to choose individually between several alternative proposals. Although Kuhn does not say it as clearly as we are doing, the axiological component of disciplinary matrices plays a key role in scientific revolutions, precisely when the definitions of basic concepts, models and exemplars are called into question.

This does not imply that the science value system provides a decision algorithm to choose between alternative theories when a paradigm enters into crisis. Kuhn denied again and again the existence of an axiological decision algorithm. For our part, we fully agree with him on this point, as we have already argued in the book Science and Values. However, according to Kuhn, even in times of crisis the values of science remain, although their application or weighting by each individual scientist can change. “There are values that are used in the prosecution of all theories,” explicitly stated Kuhn 162. The theories alternatively proposed to solve an enigma or an anomaly “must allow, first of all, the formulation of the enigma and its solution; they should be, as far as possible, simple, self-consistent, and with respect to other commonly held, compatible and plausible theories (I think now that a weakness of my original text is the little attention given to values such as internal and external compatibility when considering the sources of crisis and factors in the theoretical alternative). There is also another kind of values – for example, science should not (or does not need) to be socially useful – but the preceding indicates what I mean “163. Although it is in passing, we call attention to this last statement, because it constitutes a common place among many scientists who are dedicated to basic research. Traditionally, technology and applied science had to be useful. Pure science, on the other hand, was guided by strictly epistemic values. Kuhn clearly expresses this topic, which has changed radically with the emergence of technoscience, although already in the era of modern science, many scientific institutions adopted the value “utility” (Royal Society, American Philosophical Association), even if only at a level of principles.

Despite the enormous interest aroused by his structure of scientific revolutions, these passages of Kuhn have hardly been commented, probably because at the time they were published (1970) the empiricist dogma of the strict separation between science and values continued to prevail . However, they have a great importance for the axiology of science and, as far as technosciences are concerned, they will be very useful in order to clarify some of the differences between science and technoscience.

Let’s see it In the first place, it is clear that rigor, coherence (internal and external) and simplicity play an important role when evaluating theories, even when these theories are incommensurable from the point of view of knowledge, that is, in the cases of crisis of a paradigm and scientific revolutions. Being transparadigmatic, these values, and others that could be mentioned (such as fertility, taking up the thesis of Lakatos), can be decisive to guide the individual decisions of scientists: abandon or not a paradigm, choose one or another alternative theory. Unlike Feyerabend, for Kuhn not everything goes. There are axiological criteria that, even in the middle of a crisis of the paradigms, guide the judgment of the scientists and, what is more important, their actions. A theoretical proposal that is imprecise, incoherent, incompatible with other theories that are not in crisis, inane, etc., will normally be rejected by scientists, and this at the height of a scientific revolution, when normal science is falling apart. The values bring a certain stability to science even in the revolutionary epochs. The Kuhnian thesis of incommensurability is thus tempered by the axiological components of the disciplinary matrices.

However, at such times the values are not applied equally by all scientists, but different valuations are produced. For some, coherence will prevail (think of Berkeley criticizing the Infinitesimal Calculus for being contradictory), for others fecundity (Euler barely bothered about the foundations of Calculus and brilliantly used the new mathematical technique to solve multiple physical and mathematical problems), for others the novelty or the amazement at the surprising and promising of the new proposals (case of the Einsteinian program against the Lorentz one, or the subjective attitude of the Cantor himself before the demonstration of the biunivocity between the integers and the rational ones). The values of science continue to be shared at such times, but the axiological priorities of scientists diverge, or at least their respective weights. Kuhn always complained that, when he alluded to the values of science and its different subjective application, he received an avalanche of criticism, accusing him of subjectivism, if not irrationalism. However, his position on this problem, which is one of the most delicate of the philosophy of science, was always the same, although its nuances were not understood at that time:

“Values can be shared by men who differ in their application to a greater degree than other kinds of components of the disciplinary matrix. Accuracy judgments are relatively stable, though not entirely, from one time to another, or, in a particular group, from one member to another. But the judgments of simplicity, compatibility, plausibility, etc., often vary enormously from one individual to another “…” And most importantly, values would often dictate different alternatives in these situations where different values should be applied , taken in isolation. 

One theory may be more accurate but less compatible or plausible than another; again the old quantum theory gives us an example. In short, although the values are widely shared by scientists and even when the agreements regarding these values are something profound and constitutive of science, the application of them is sometimes affected considerably by the characteristics of the personality individual and by the background of the scientist, what individualizes and differentiates the members of the group “164.

We extract some consequences of these theses of Kuhn, that seems to us correct:

1.- Values are constitutive of science, not alien to it. Obviously, Kuhn alludes to epistemic values, among which, it must be emphasized, he never mentions the value “truth”, or even “verisimilitude”.

2.- The values of science constitute a system, they are not considered in isolation. In our own terminology, Kuhn is opposed to axiological monism and prone to a joint consideration of several epistemic values before issuing a judgment on the acceptability or rejection of a theory.

3.- The scientists apply some or other evaluation criteria to the theories. For our part, this point is very important. The values have to be characterized as functions in the freigo sense of the term.

4.- It is not the same to share a definition, a mathematical formula, a model or a paradigmatic example that share a system of values. In the first cases, these components are accepted or not, which are part of the “hard core” of the theories. In the case of values, they are also shared, but not 100%. Its application is a matter of degrees. This is one of the reasons why we strongly affirm the gradual nature of values.

5.- In such cases, rationality does not consist in emitting coincident judgments based on a single valuation criterion, but in weighing and debating the various valuation criteria, that is, in weighing more or less the various values. The axiological rationality differs considerably from the rationality based on the attribution (or not) of properties to things, as Kuhn’s text shows and as, for our part, we have emphasized more than once 165. It is a deliberative rationality and plural, and this necessarily, because it is subject to several requirements of acceptability, not to only one.

In the case of technosciences, the situation is structurally different, because the subject of technoscience is plural and the various agents that compose it do not even share the same value systems. Hence, conflicts of values are inherent to techno-scientific activity, unlike science, where they only manifest themselves in times of crisis and revolution. The axiological issues do not seem to exist in the normal science epochs, precisely because there is a system of shared values whose respective weighting has been normalized, to a greater or lesser degree. In the case of technoscience, this is not the case, because not a single community intervenes, but several, each with its own subsystem of values (epistemic, technical, economic, military, political, social, ecological, etc.). Paraphrasing Kuhn: Techno-sciences in normal times also present conflicts of values, because heterogeneous communities intervene actively in technoscientific activity, usually represented by concrete agents that embody their respective values and, where appropriate, interests. Therefore, conflicts of values are “connatural” to the techno-scientific activity. Different question is the way to solve them, or to reach at least points of equilibrium. On this we will return later.

To conclude with this brief comment to Kuhn, we will mention another passage about the values of science. It deals with the debated question of the subjectivity or objectivity of values. Contrary to those who tried to banish all traces of subjectivity in the valuations of scientists, Kuhn considered that this recourse to the subjective can be very beneficial in times of paradigm crisis:

“Individual variability in the application of shared values can serve as an essential function of science. The points where the values should be applied are also, invariably, those where risks are taken. Most anomalies are solved by normal means; Many proposals for new theories turn out to be wrong. If all the members of a community responded to each anomaly as a source of crisis, or admitted each new theory promoted by a colleague, science would stagnate. If, on the other hand, nobody reacts to the anomalies or to the theories of recent edition in highly risky form, there would be few or no revolutions. In matters such as these, recourse to shared values rather than shared rules that direct individual choice may be the way for the community to distribute risks and ensure the success of its long-term activities “166.

Kuhn does not reject subjective evaluations because he thinks they can contribute to improving intersubjective values, or at least their application. Although he never developed an axiology of science, limiting himself to making these kinds of considerations, we can interpret that he perceived very well the differences between epistemology, methodology and axiology, then established by Laudan and his reticular model 167. The methodology could consist of a set of rules that, applied systematically, lead to certain and certain results. The axiology does not work like that. The axiological functions can be applied differently by the evaluating agents, or if it is preferred by the scientists who decide to opt for one or the other theory. With several evaluation criteria, the problem of finding the result of this plurality of evaluation actions arises. Faced with the monistic conceptions of rationality, based on the maximization of a value (truth or verisimilitude in the case of science, efficiency in technology), Kuhn can be considered a precursor of plural axiological rationality that we We advocate 168. We will return to the debate in the fourth chapter.

After this excursus on the Kuhnian conception of the values of science, we have left to comment the fourth and last component of its paradigms, the exemplars, that is, the solutions of problems that have been accepted as valid solutions by the scientific communities. In the case of technoscience, these specimens have a technological specification: a certain algorithm that solves a computational problem, an apparatus that improves the accuracy of observations or measurements, a great equipment that increases speed, the ability to calculate or the possibilities of experimentation, a company that fully assumes the new structure of scientific practice, etc. In a word, although the construction of these specimens is based on several scientific theories, we are dealing with technological resolutions of the problems, not with theoretical solutions. There are no properly scientific specimens, but techno-scientists. Some take the form of apparatuses, others, on the other hand, are models of organization and functioning of a techno-scientific company that has offered good results in a certain country or area of knowledge and that, immediately, is imitated and considered as an organizational model that solves first of all problems linked to scientific practice. The canonical specimens of technoscience are artifacts, some of them physical, others intellectual, others of social organization and management of the techno-scientific activity. In any case, they solve problems of scientific practice, rather than theoretical problems.

III.4: The techno-scientific paradigms.

After this brief review of the Kuhnian conceptions, it is now a question of exploring to what extent they are valid for technoscience, not only for science. From what has been said up to now it can be inferred that the Kuhnian model for scientific revolutions has to be expanded and modified in several points to try to apply it to the techno-scientific revolutions. Kuhn distinguished between symbolic generalizations, models, values and exemplars of a paradigm. In this section we will explore whether these concepts are still valid in the case of technosciences.

In this regard, it is worth remembering one of the differences between science and technoscience: the latter implies, above all, changes in scientific practice, not only in knowledge. Therefore, it is necessary to distinguish between symbolic generalizations, models, values and exemplars from two perspectives, theoretical and practical. In this way, the notion of paradigm is extended, because it includes both dimensions.

With respect to symbolic generalizations, scientific languages still exist, but they are superimposed on a new modality of language, technolanguages or infolanguages. Scientific concepts and terms, whether theoretical or observational, continue to perform their referential and semantic functions. Technoscience maintains a linguistic component when it is formulated, since it is still science. However, classical scientific languages are superimposed on technolanguages, which are the most commonly used in research practice. The multiple software variants that are used to control the functioning of scientific instruments are a good example of symbolic generalization necessary for techno-scientific practice, since many of the activities (calculate, observe, measure, experiment, even demonstrate) are not possible without those computer tools. Normally, they are very different according to the disciplines and the research lines. Mastering them is an indispensable requirement to be able to investigate, because the data, hypotheses and results are expressed according to technological formats. In some subjects powerful computing instruments are used, in others it is essential to master the techniques of scientific visualization. Taken together, technolanguages can be considered as symbolic Kuhnian generalizations of technosciences. Note that these technolanguages can also be used for organizational, management and evaluation issues. Computer languages affect all phases of techno-scientific activity, not only in research.

The new structuring of scientific practice generates new formal instruments that, as they become national or international standards, can be considered as symbolic generalizations that order the scientific practice itself. We saw that techno-scientific companies are much broader and more complex than the observatories, laboratories and cabinets of classical scientists. In addition to laboratory protocols and articles for scientific journals, technoscientists must be able to properly complete other types of documents: forms to request research projects, evaluation reports, spreadsheets, patent contracts, etc. This second type of symbolic generalization is not scientific, but economic, administrative and legal, but we have already seen that bureaucracy and management are a fundamental part of techno-scientific companies. Its existence and its generalization in a country or in a certain discipline reveal the implantation of technoscience.

Normally, this type of demands are tedious for researchers, although they are essential to carry out, given the current structure of scientific activity. It is common for large research teams to include people specialized in this type of skills and abilities, which do not concern scientific knowledge, but rather practice. There are also frequent cases in which the researchers themselves have to learn to competently use this new type of instruments, which are not observation or experimentation, but management. The establishment of scientific policy systems always leads to the creation of standardized instruments for the management of science and technology. Although they may seem less important than classical scientific instruments, the fact is that in technoscience they are fundamental, due to the very structure of science and technology systems, which require all the research teams to use these protocols at the same time. make proposals, issue reports and present results. In a word: the management and administration of techno-scientific companies generate new symbolic generalizations, usually computerized: the EXCEL calculation sheets, the computer platforms for presenting and evaluating projects, etc. This new modality of symbolic generalization was unthinkable in the era of modern science, but today it consumes a good part of the efforts of technoscientists. The mastery of these techniques is an indispensable requirement for an investigation to be successful, to a degree no less than the mastery of traditional scientific languages. The systems of science and technology indicators, essential in the scientific policy cabinets, can be considered as another modality of symbolic generalization. The analysis of these indicators and, above all, the changes they undergo, provides a good indication of the existence of dominant paradigms in techno-scientific practice.

As regards the theoretical models, there are no great variations, except in some concrete sciences, such as cosmology and biology, in which scientific revolutions have taken place in the Kuhnian sense of the term, in addition to the praxeological revolutions to which we refer to On the ontological level, technoscientists ascribed to the same paradigm share a basic ontology, as do scientists. The omnipresence of computing privileges computer models, but this is comparable to what happened in modern science, when mechanicism was a predominant ontology. Evolutionary models are also dominant, as shown by the fact that the computer tools themselves are distinguished according to generations, as well as many other techno-scientific devices. Systems theory is another of the great ontological models of technoscience, for example in the case of cybernetics and in the technosciences that derive from it.

However, as far as the practice is concerned, other types of models appear: the so-called “good practices”, which quickly become canonical for other institutions and techno-scientific companies. Benchmarking is a common practice in techno-scientific companies, which allows the configuration of authentic models for scientific practice: ways of organizing research activity, managing patents, establishing networks of laboratories or consortiums between libraries and research centers, etc. In section II.3 we had occasion to refer to some of these models of technoscientific practice.

The biggest change between science and technoscience refers to values, as we saw in the previous section. There are still values that guide techno-scientific actions, but these are not shared by all agents, which is why axiological conflicts are continuous. In addition, the value systems that guide techno-scientific activity are much more complex and plural, so a proposal or result has to overcome several instances of evaluation to be considered as a contribution of interest. That is why we attach so much importance to axiology when it comes to distinguishing between science and technoscience, as we will see in greater detail in chapter 5.

Finally, the Kuhnian notion of copies is still valid, although with the nuances that we have already seen. These specimens take the form of technological artifacts that have proved extremely useful for solving problems, becoming canonical for scientists, but also for society itself. Sooner or later, many of the canonical artifacts used by scientists are transferred to civil society, adapting them to the new uses that it requires. The most novel are those that deal with the organization of scientific activity, as we have indicated previously. They are techno-social artifacts and are often studied by social technosciences. Structured systems of science and technology are a typical example.

We can conclude, therefore, that the notion of “paradigm” can continue to be used in philosophy of technoscience, although with nuances and significant variations, if we compare it with the Kuhnian notion. Generally speaking, it can be said that techno-scientific paradigms overlap with scientists, introducing new components, such as ways of organizing and managing the processes of obtaining knowledge. In the same scientific discipline there may be people who, accepting the same scientific paradigm in regard to theories and methods, differ completely in terms of techno-scientific paradigms. Not all physicists are technophysical, nor are all biologists technobiologists. Agreeing on the basic postulates of their respective sciences, they may be radically at odds with the way of designing and organizing the research activity.

III.5: From scientific revolutions to techno-scientific revolutions.

The Kuhnian notion of “paradigm” must be expanded, nuanced and modified. The same can be said in the case of scientific revolutions:

1.- The techno-scientific revolutions suppose a deep change in the scientific and technological practice, that affects the structure of both. Just as the philosophers of science emphasized the existence of a structure in scientific knowledge, in order to investigate technoscience, it is necessary to clarify the structure of technoscientific activity in the first place. The techno-scientific revolution is not, prima facie, an epistemological or methodological revolution (methods and scientific knowledge continue to exist and apply), but above all a praxeological revolution.

2. Throughout the twentieth century, macro-science and technoscience have produced numerous theoretical changes, and even revolutions in the Kuhnian sense of the term. This has happened in cosmology, in biology, in chemistry and in many other scientific and technological disciplines, some of which are new. However, when analyzing the techno-scientific revolutions we should not focus on those theoretical or methodological changes, but above all on the praxiological changes. The important thing is to locate the changes in the scientific practice and in its organization, as well as the insertion of sectors and groups of the scientific communities in diverse techno-scientific companies, be they public or private, civil or military. These transformations occur first in very specific universities and research centers, for example at MIT, Stanford or Berkeley in the 1930s, or also in some industrial companies that create R & D departments (such as Du Pont in the 30s). This would be the pre-revolutionary phase, in which the new techno-scientific paradigm is emerging, in this case macro-science. During the Second World War this process became widespread. That is why we date the first techno-scientific revolution in this era. But what was decisive was the consolidation of this new structure of scientific practice, which is achieved with the creation of a new science and technology system in the US in the immediate post-war phase. The maintenance after the war of a scientific practice based on the close collaboration between scientists and engineers, in the appearance of R & D companies, in the subordination of the purely scientific or engineering objectives to the objectives indicated by the financiers of the macroprojects, etc., is the key to determining the moment in which the techno-scientific revolution took place. When this new structuring of scientific and technological activity was transferred to other countries, always starting with specific centers and companies, it was when the techno-scientific revolution spread to these countries, without prejudice that there might be precedents in some European countries (Great Britain, Germany, France) of this new way of doing science. The same can be said of the Soviet Union, where a detailed historical study would have to be made in order to clarify the way in which the techno-scientific revolution took place there after the Second World War. It can be said, in any case, that the emergence of centralized and coordinated scientific policies in various countries, together with the creation of large national science and technology agencies, are institutional signs that the techno-scientific revolution was beginning to take place.

3.- Since the notion of the scientific community is basic to the Kuhnian reflection on revolutions, it can be affirmed that the greatest insufficiency lies in that notion. In the age of technoscience, the scientific and engineering communities are superimposed on another type of social agents (political, military, business, etc.) that play a decisive role in techno-scientific activity. Generically speaking, the emergence of techno-scientific companies is one of the signs that mark the arrival of technoscience. Wherever a university department or a research center becomes a company, public, private or mixed, and is acquiring forms of organization and clearly operating business, it should be noted that the transition from science to technoscience is taking place, without prejudice to that these organizational mutations may fail later. This regardless of the discipline in which such a transformation occurs. Technoscience implies, above all, a new way of organizing scientific and technological activity. The personal evolution of scientists like Vannevar Bush, John von Neumann, John Watson or Craig Venter illustrates this thesis well.

Observe that the object of study for the history and philosophy of science changes radically. In the case of the Kuhnian scientific revolutions, one had to be alert to the emergence of new theories and new methods, because they were epistemological and methodological revolutions. Techno-scientific revolutions, on the other hand, are first and foremost praxiological. It is about investigating the moment in which the new structure of scientific-technological practice is imposed in a university, research center, company or country. The appearance of Big Science was a change of this type, and for that reason it has to be considered as the first emergence of technoscience. In the last decades of the twentieth century there was a second techno-scientific revolution, characterized by the widespread introduction of computer technologies in laboratories, observatories and research centers. That is why we distinguish these two types of techno-scientific revolutions in the 20th century, without prejudice to the fact that a more detailed historical study could make it possible to discern other forms of emergence of technoscience.

III.6: From the incommensurability between theories to the incompatibility between techno-scientific systems.

Our divergences with Kuhn point to the core of his conception of scientific revolutions, which ended up focusing on the problem of incommensurability between paradigms, and in his later writings in a linguistic version of incommensurability, based on the notion of untranslatability: “affirm that two theories are incommensurable means to affirm that there is no language, neutral or of any other kind, to which both theories, conceived as sets of statements, can be translated without remnant or loss “169. Kuhn called local incommensurability to this last version of his thesis, which so many rivers of ink has made since the publication of his book Structure of scientific revolutions. It is a semantic incommensurability, in which the terms used by one or other scientists do not mean the same thing. In the case of techno-scientific revolutions, it is preferable to speak of incompatibility between technological systems than of incommensurability between theories:

1.- The incompatibility between technosystems affects above all the scientific-technological practices, including the agents, instruments and objectives of their actions. results that are derived from them. Although they later converge in terms of knowledge, the “rival techno-scientific paradigms” differ radically from each other in procedures, techniques, styles of action and the organization of scientific activity. There is “practical incommensurability”, not only theoretical, and this gives rise to opposing and incompatible techno-scientific cultures. For example, there are techno-scientific companies in which the secret and the principle of hierarchy prevail. It is the most frequent in the case of investigations of a military nature. Others, on the other hand, are much more open and cooperative. Both compete hard against each other when it comes to obtaining financing, obtaining prestige, exploiting patents and achieving the primacy in the market of derivative techno-scientific products. If a thorough study were to be made, the contrast between Soviet and North American macro-scientific research during the Cold War would illustrate these differences well.

2 .- As argued by the defenders of the semantic conception in philosophy of science (Suppes, Sneed, Moulines, Van Fraseen, Giere and others), scientific theories are not sets of linguistic statements, but classes of models, in particular models mathematicians In the case of technoscience, this non-linguistic conception of the theories and results of research is literally essential. Technoscience also has a very important theoretical component, which is usually expressed in the form of computer models and technological artifacts that are “exemplary” (in Kuhn’s sense) of “techno-scientific paradigms”. Many techno-scientific innovations do not even take the form of more or less credible theories from an empirical point of view. They are apparatuses, software, action techniques and organization. The techno-scientific incommensurability is very different from that of scientific theories and therefore it is preferable to speak of incompatibility between alternative or rival technological systems.

3.- Both mathematical and non-mathematical formulations of scientific theories, however incommensurable they may be, can be expressed in the same computer language. This does not imply that the incommensurable terms or concepts among themselves come to mean the same thing. However, the digitalization and computerization of the data requires the existence of common standards and protocols, without which the computer representations are strictly incompatible with each other. The serious problem arises when the computer and digital representations are incompatible with each other. The techno-scientific incompatibility opens a greater abyss than the incommensurability between theories because it affects practice and actions, not only theories and images of the world.

III.6: From the incommensurability between theories to the incompatibility between techno-scientific systems.

Our divergences with Kuhn point to the core of his conception of scientific revolutions, which ended up focusing on the problem of incommensurability between paradigms, and in his later writings in a linguistic version of incommensurability, based on the notion of untranslatability: “affirm that two theories are incommensurable means to affirm that there is no language, neutral or of any other kind, to which both theories, conceived as sets of statements, can be translated without remnant or loss “169. Kuhn called local incommensurability to this last version of his thesis, which so many rivers of ink has made since the publication of his book Structure of scientific revolutions. It is a semantic incommensurability, in which the terms used by one or other scientists do not mean the same thing. In the case of techno-scientific revolutions, it is preferable to speak of incompatibility between technological systems than of incommensurability between theories:

1.- The incompatibility between technosystems affects above all the scientific-technological practices, including the agents, instruments and objectives of their actions. results that are derived from them. Although they later converge in terms of knowledge, the “rival techno-scientific paradigms” differ radically from each other in procedures, techniques, styles of action and the organization of scientific activity. There is “practical incommensurability”, not only theoretical, and this gives rise to opposing and incompatible techno-scientific cultures. For example, there are techno-scientific companies in which the secret and the principle of hierarchy prevail. It is the most frequent in the case of investigations of a military nature. Others, on the other hand, are much more open and cooperative. Both compete hard against each other when it comes to obtaining financing, obtaining prestige, exploiting patents and achieving the primacy in the market of derivative techno-scientific products. If a thorough study were to be made, the contrast between Soviet and North American macro-scientific research during the Cold War would illustrate these differences well.

2 .- As argued by the defenders of the semantic conception in philosophy of science (Suppes, Sneed, Moulines, Van Fraseen, Giere and others), scientific theories are not sets of linguistic statements, but classes of models, in particular models mathematicians In the case of technoscience, this non-linguistic conception of the theories and results of research is literally essential. Technoscience also has a very important theoretical component, which is usually expressed in the form of computer models and technological artifacts that are “exemplary” (in Kuhn’s sense) of “techno-scientific paradigms”. Many techno-scientific innovations do not even take the form of more or less credible theories from an empirical point of view. They are apparatuses, software, action techniques and organization. The techno-scientific incommensurability is very different from that of scientific theories and therefore it is preferable to speak of incompatibility between alternative or rival technological systems.

3.- Both mathematical and non-mathematical formulations of scientific theories, however incommensurable they may be, can be expressed in the same computer language. This does not imply that the incommensurable terms or concepts among themselves come to mean the same thing. However, the digitalization and computerization of the data requires the existence of common standards and protocols, without which the computer representations are strictly incompatible with each other. The serious problem arises when the computer and digital representations are incompatible with each other. The techno-scientific incompatibility opens a greater abyss than the incommensurability between theories because it affects practice and actions, not only theories and images of the world.

4.- We do not enter into the debate about translation. For the moment, it is enough for us to make possible a transliteration of the different systems of scientific and technological signs to the binary system. 170. Well, this is one of the main virtues of computer languages. Not only the transliteration between natural languages or the translation of speech to signs written by means of automatic voice recognition techniques, but also the automatic transfer of data, sounds and images to each other. The great methodological novelty of technosciences lies in the possibility of resorting to computer simulations, for example by representing formulas and databases through images and sounds, and reciprocally. Diagrams and Cartesian representations of mathematical functions are possible, but, in addition, it is possible to represent non-linear functions informally, so that scientists have images and data that were not accessible by traditional mathematical techniques. The digitalization and computerization of natural languages, mathematical formulas, scientific tables, images, movements and sounds is one of the engines of the techno-scientific revolution, because it considerably increases the capacities for scientific action. In Kuhnian terms: we can speak of new symbolic generalizations (infosymbolic, in this case), although these are very different to those that characterized the paradigms of modern science. In our own terms: the most developed technosciences are infociencias, just as the mathematized sciences supposed an advance with respect to the unmathematizable in modern science. Of course, the mediation introduced by technolanguages is very different from the mediation of the natural and mathematical languages in which the sciences are expressed.

III.7: From scientific controversies to techno-scientific controversies.

Since Kuhn defined the notion of scientific paradigm and affirmed his disputed thesis about the incommensurability of alternative paradigms, philosophers, historians and, above all, sociologists of science have paid much attention to scientific controversies. Previously to Kuhn, those episodes were considered as lamentable incidents inside the scientific communities. From Kuhn, however, controversies illustrated the confrontation between paradigms and therefore had to be studied and analyzed in depth.

If we accept that part of contemporary science is technoscience, we will have to ask ourselves about the differences between scientific and techno-scientific controversies. In this section we will try to show that the distinctive features pointed out in sections II.1 and II.2 offer us a good guide to differentiate both types of controversies. We will say therefore that:

a): Since technology tends to transform the world, not only to know what it is like, a techno-scientific controversy implies two or several alternative ways of transforming the world. American and Soviet science after the Second World War are two good examples, and this in several areas: nuclear energy, exploration of space, development of weapons and defense systems, industrial research, etc. The competition between alternative computer systems (for example Windows and Linux) constitutes a more recent example, as does the race between the public PGH and the Celera Genomics company to map the human genome. Since the oppositions between alternative techno-scientific paradigms are not purely discursive, but are developed by transforming the world through effective practices, the term “controversy” has to be replaced by “conflict”. In some cases, these conflicts do not go beyond the scope of scientific policy. In others they develop in the market, in the form of competition between rival techno-scientific companies. But we must not forget the links between technoscience and military activities. Examples of competing macro- and ten-scientific projects abound during the Cold War, and even in battlefield operations. The Hiroshima and Nagasaki bombs are the first example, but not the only one. Therefore, there are occasions when techno-scientific “controversies” become military conflicts, which are resolved according to the greater or lesser capacity of destruction of the devices manufactured by the enemy, be they airplanes, submarines or telecommunications networks. When the power of technoscience is destructive, whoever possesses the greatest capacity for destruction wins.

b): The rival techno-scientific paradigms struggle in particular to transform science itself. One of the central points of opposition is to show that the new techno-scientific paradigm radically improves scientific practice and promises enormous advances in terms of knowledge. It always insists on the enormous possibilities that each techno-scientific paradigm opens for science, and in its case for society. Frequently a kind of universal salvation is promised, a promised land if the nascent paradigm is duly promoted against the previous one. This happened with nuclear energy, with the conquest of space, with computers, with techno-statistics in the social sciences, with the Internet, with the genome project, with genetic engineering, etc. In each and every one of these cases, the new paradigm promised immense advances for science and for society. At the same time, it generated concern about the consequences that could arise, and therefore opposition. Techno-scientific controversies often arise in terms of technophilia and technophobia, especially when they reach society. We have affirmed that technoscience not only transforms nature, but also society. The conflicts that stem from that attempt can be considered as another kind of techno-scientific controversy.

c): The techno-scientific activity requires great equipment to develop, which is why controversies usually take specific forms: some try that such and such large equipment be financed and built, others oppose it, considering it an economic waste whose benefits are to see, and support alternative projects, always insisting on their highest priority. The debate in the US on Supercollider Supercomputer is a canonical case. These controversies go beyond the scope of academic and scientific discussion, taking place in scientific policy offices, in the R & D departments of companies, in parliaments and, where appropriate, before the courts. Frequently they divide the scientific communities, but not for epistemic reasons, but praxiological ones. Therefore, techno-scientific controversies do not occur in scientific journals and books, but in offices and agencies where they struggle to obtain adequate financing for macro-projects and the new institutions that would have to be created to develop them. They are resolved in favor of one or the other through scientific policy actions and decisions (public or private), not through a methodological or epistemological debate. It is interesting to note that many of these contests are about the priority issue, but not in discovery, as in modern science, but in funding. Many conflicts occur before the investigations are launched, that is, in the pre-action and design phase. The cost of projects is usually an important factor to take into account when arguing for or against, regardless of the scientific excellence that may arise from one or other projects.

d): Techno-scientific controversies always have an economic aspect, often the most important one. The establishment of priority funding lines is often decisive between rival techno-scientific paradigms. We will say therefore that this type of controversies always have a budgetary reflection. The numerous failed techno-scientific revolutions (for example, high-definition television) leave a trace of economic waste. They are significant cases to study. In any case, there is no techno-scientific revolution without strong and decisive economic support, that is, without substantial investments. It was one of the characteristics of macroscience, but it continues to be so in technoscience, to a greater or lesser extent.

e): Instead of circumscribing a conflict between scientific and technological communities, revolutionary changes are usually carried out by companies or by government agencies that operate according to business models of management. A technoscientific community that intends to promote an important change will have to look for public or private funding sources for it and introduce new models of allocation and management of resources. The expectation of further benefits (economic, social, political, etc.) plays a very important role, notwithstanding the fact that epistemic and technological benefits can also be expected. A techno-scientific revolution is never made out of pure love of science and knowledge. Other value systems are always involved, particularly economic ones. According to the entrepreneurial nature of the techno-scientific activity, a revolution of this kind requires some type of marketing, be it political, business or social. Without these skills, a techno-scientific revolution does not triumph, independently of the fact that epistemic contributions (discoveries) and relevant technological innovations are also required. The novelty is that the great changes in knowledge are not enough to provoke a revolution.

f): The subject that carries out the techno-scientific revolutions is not an individual subject (like Einstein or Mendel), but a set of social agents. The bonds that hold them together are diverse, but the existence of stable ties and strategic alliances between diverse unions (scientists, technologists, politicians, businessmen, military, etc.) are an indispensable factor for the progress of a techno-scientific revolution. These links are transdisciplinary, unlike scientific revolutions. According to what was said in the previous paragraph, they include agents who are experts in the communication of knowledge to society, or at least their leaders. Hence the crucial importance of the dissemination and reception of techno-scientific innovations, which is manifested in the market, on the one hand, but also at the level of opinions and attitudes of the various social sectors.

g): The public plays an important role in techno-scientific controversies, and not only for the favorable or unfavorable image that is made of the new proposals, but above all as a future user of the innovations that result. Sooner or later, the conflict between two or more techno-scientific paradigms is mediated by the greater or lesser acceptance of the public to their derivative proposals. In most cases this translates into technological artifacts that compete in the market. Since these technological innovations transform the capabilities of human action, the greater or lesser acceptance by society of these modifications becomes one of the criteria for the elucidation of disputes. Note that, since there are different types of public and companies, techno-scientific innovations may have a greater or lesser degree of acceptance and diffusion in one or other societies. The most important technological revolutions (rail, automobile, household appliances, etc.) crystallized in the context of application, when these technologies acquired wide diffusion in several countries. In the case of technoscience, the public is only one of the instances of partial resolution of controversies, together with political, business, institutional, etc. But its role is usually important in the case of the most important techno-scientific innovations.

h): From an axiological perspective, techno-scientific controversies always involve value conflicts in several axiological subsystems, not only in the subsystem of epistemic values. This is because technoscience transforms the world, and more specifically societies. Therefore, techno-scientific changes often have social, political, ecological, legal, etc. consequences, not only epistemic, technological or economic. In some cases they have military derivations and moral and religious implications. On these occasions, techno-scientific controversies tend to be radicalized (military conflicts, refusal to act technoscientifically on the basis of religious beliefs or moral principles). They are the most interesting examples for an in-depth axiological analysis, because they involve different value systems and different agents that promote or prioritize one or other subsystems of values.

i): The fact that technoscience is based on information technology means that, in general, techno-scientific controversies are manifested in the form of opposing and alternative computer proposals. Therefore, in order to choose case studies, it is convenient to look at those controversies that manifest themselves in the form of incompatible computer products (configuration, processing, navigation, storage systems, etc.). Information technologies are a very suitable field for the study of techno-scientific controversies.

On the whole, techno-scientific controversies overflow the notion of controversy: they are contentions, sometimes in the literal sense of the word (military combat), sometimes in a figurative sense: political, economic, social, legal conflicts, etc. They develop in markets, in companies, in institutions, in political media, in society, in the media, and sometimes also in the field of Mars. In such cases, techno-scientific agents are military, for example, states that fight to be great powers and therefore invest heavily in research and development. In general, techno-scientific contests are fought by conglomerates of social agents (lobbies). Therefore, a techno-scientific community that seeks to promote a new paradigm has to ally with other types of social agents. It is no longer enough to control scientific societies or academic power to impose a controversy, as in Newton’s time. Techno-scientific contests develop in many other scenarios and permeate society, sooner or later. Hence, the social component, along with the economic, technological and epistemic, are the four minimum facets to be considered in these controversies. When these controversies become military conflicts, their resolution in the battlefields is usually particularly dramatic and destructive, both for the environment and for the societies involved in the conflict.

In all these cases, we are facing technological systems that are incompatible with each other, in the sense of non-integrable, non-compostable. This would be the techno-scientific transcript of what Kuhn called incommensurability between techno-scientific paradigms. Note, however, that this initial incompatibility is usually alleviated with the course of the

weather. It is also important to emphasize that in the case of techno-scientific contests, the defenders of one or the other paradigm have no qualms about spying on innovations, copying them and appropriating them or using benchmarking strategies. The business impregnation of technoscience results in the combat between techno-scientific paradigms resorting to tactics and strategies very different from those used by the scientific communities in their polemics.

What has been said above must be considered as a first contribution to the subject of techno-scientific controversies. It is about opening a new field of research to science and technology studies, be they philosophical, historical, sociological, political, economic, social, ecological, moral or otherwise. The previous proposals have to be confronted with case studies from the different technoscience modalities. These case studies will allow to correct and improve the preceding suggestions.

Chapter IV

Techno-scientific systems

IV.1: Structure of the techno-scientific practice.

The philosophers of twentieth century science have thoroughly analyzed the structure of scientific knowledge, distinguishing theories, laws, hypotheses, concepts, facts, etc. The inherited conception focused on the linguistic expression of this knowledge, both in natural languages and in mathematical formalizations. The semantic conception continued accepting that theories are the keys of vault of the scientific knowledge, although it happened to analyze them like classes of models, more than like linguistic entities. In recent years new trends in the philosophy of science have emerged: some emphasized the social component of scientific and technological knowledge, including theories, others pointed to the importance of experimentation in obtaining scientific knowledge, criticizing the primacy of theoretical aspects and showing the relevance of experimental tradition in the history of science. Of course, there are many other remarkable trends, which is not the case here listed 171, both in the strict field of philosophy of science and technology and in the more general science and technology studies.

In this chapter we propose to open a new topic for philosophical and interdisciplinary research: to analyze the structure of technoscientific activity. It is a complex issue, because it concerns very different spheres of science and technology, as we have seen in the first two chapters of this book. The proposals that we are going to make next will necessarily be provisional. They will focus on the elucidation of two concepts that we think are necessary for the philosophy of technosciences: techno-scientific systems and techno-scientific actions. These actions are produced within the framework of various techno-scientific systems, so it is necessary to know the structure of the latter to analyze the structure of the techno-scientific activity. We do not doubt that further research will improve these proposals without difficulty and will add other important concepts that are not considered here.

We will only deal with the first epoch of technoscience, as it was configured in the USA at the time of the Second World War. An analysis of the establishment of the system that started and then sustained the macro-science, even if it is superficial, will allow us to delimit several structural components and analyze some relationships between these components. We will start from a systemic conception of technoscience, and therefore holistic. Technoscience requires the constitution and consolidation of science and technology systems (SCyT), of which many other subsystems are part (institutions, companies, agents, equipment, innovations, etc.). But, in addition, we will add an analytical methodology, based on the distinction of basic components of the SCyT system and its integrated subsystems, as well as the techno-scientific actions that are carried out in these systemic frameworks. This analytical system will be concretized in the axiology of technoscience, which will be dealt with in the next chapter.

The progressive implementation of the SCyT system offers several variants depending on the countries and disciplines. This system generates a new form of culture, the techno-scientific culture, which enters into a relationship (and sometimes a collision) with previously existing cultures, including modern scientific culture 172. The components that we are going to distinguish present different variants according to disciplines and systems. SCyT of each country. Even so, there is a general structure that is common to all of them, to a greater or lesser degree. The aim is to elucidate the basic components of this structure, in order to present a first analysis of it, which will subsequently have to be refined and improved, contrasting these conceptual proposals with the specificities of each specific scientific-technological system.

With these caveats, there are several tasks to be carried out. In the first place, it is necessary to define the framework in which the techno-scientific activity takes place. Secondly, it is necessary to specify who are the most relevant techno-scientific agents and what are the characteristic actions of technoscience. Third, we need a theory of techno-scientific actions: we will start from the proposals we have made in the book Science and Values 173. There are other structural components to be distinguished, but the study of these three first ones (S & T system, basic agents and types of actions) together with this theory of action will allow us to clear something of the structure of techno-scientific practice. We will analyze and comment on some of them, not all of them. The topic we are dealing with is very broad and it is about taking some first steps in your study, not reaching the end, much less exhausting it.

IV.2: The emergence of scientific policy.

We saw in Chapter 1 that the macro-sciences arose at the time of the Second World War in the USA. Other countries (Germany, Great Britain) were oriented in a similar direction, although the war prevented the consolidation of the technosciences in them. We also saw that they arise first in the field of physics and mathematics, based on the needs of basic research (cyclotrons, computers) or military activity (radars, trajectories of projectiles, atomic bombs …). These first macroprojects were successful and enabled the development of many others. The alliance between scientists, technologists, military and industrialists proved mutually beneficial, without prejudice to the conflicts that arose, reason why the US Government decided to institutionalize and politically lead said alliance, converting it into a strategic alliance. To this end, the American scientific and technological system was remodeled.

It is usually attributed to Vannevar Bush and his 1945 report, Science, the Endless Frontier 174, the basic design of the North American SCyT system. For our part, we believe that the approval and implementation of the guidelines of this report synthesize the initial phase of macro-science well, despite the fact that authors such as Greenberg have ridiculed the myth of the “creator” of the new science and technology policy, providing some arguments against this founding myth 175. It is true that some North American universities (MIT, Berkeley, Stanford) had already taken steps in that direction. But the extension of this model to the whole country, together with its parliamentary approval for the post-war period, were decisive steps for the consolidation and development of what had already been tried before.

The Bush report interests us as a design of a new framework for scientific and technological activity in the postwar period and also as a theory about the influence of science on society. The design phase, by the way, was complicated and conflicting. The defenders of the previous scientific-technological tradition in the USA (priority of the States before the Federal Government, distrust regarding the intervention of the Government in scientific matters, search of private patrons to support the Universities and research centers, etc.) They opposed considerable resistance to the new ideas, so Bush needed strong political support to be able to carry out his proposals. Even so, Truman took more than four years to implement them. It is important to underline that, once published, this report was a very important macro-scientific action, although it was not done in a laboratory, but in a new scenario of macro science, the scientific policy office and its environment, that is, the White House, the House of Representatives and the Committees that advised Bush 176. The objective of this action was not to generate specific knowledge, but to create the conditions of possibility for it, transforming scientific practice and introducing important changes in its institutional, political framework , financial and social. It was a macro-scientific action because its objective was to transform the structure of American science as a whole. In addition, the Bush report formulated a new theory of scientific practice, which Bush had been assessing from his long experience as a scientist in the first place, and then in top institutional positions at MIT, the Carnegie Institution and the Office of Scientific Research and Development, of which he was director during the Roosevelt presidency.

In the end, the Bush report was assumed politically, after multiple controversies, debates and criticism, which did not cease after the war. Not everything proposed by Bush became a reality and, in addition to what he advocated, many other things were done. But the Bush action initiated a profound transformation of American science and technology, and this on many levels. In the immediate term, it had important institutional effects, since several of the actions suggested, such as the creation of a Scientific Council attached to the Presidency of the country and the creation of a National Coordination Agency (the National Science Foundation, as it was called) were carried out and produced lasting effects. In Kuhnian terms, the creation of the NSF (or those of NASA, the NIH, etc.) can be considered as exemplary achievements of the new techno-scientific paradigm, insofar as it transforms scientific practice. They are not the only canonical exemplars 177. If we compare this institution and its objectives with the creation of the Royal Society in the seventeenth century, we could infer many distinctive features between the scientific revolution and the techno-scientific revolution.

One of the main ones was the emergence of scientific policy, a point that Bush emphasized insistently in his report:

“We do not have a national policy for science. The government has barely begun to use it for the welfare of the nation. There is no body within it responsible for formulating or executing a national scientific policy. There are no standing congressional committees dedicated to this important issue. Science is behind the scenes. It would be necessary to put it in the center of the stage, because in it lies a great part of our hope for the future “178.

This was the main goal of the Bush report: to convince President Roosevelt and Congress of the need to design a post-war scientific policy. The text offered a theoretical foundation for this initiative, as well as a set of strategic actions to implement it.

IV.3: The Bush report.

It is important to remember that Bush, Director at that time of the Office of Scientific Research and Development, who had contributed so much to the promotion of large macro-scientific projects in times of war, wrote his report at the request of the President of the United States. In his letter of November 17, 1944, Roosevelt indicated to Bush four specific points to which he had to answer:

“(1) What can be done in a manner consistent with military security and with the prior approval of the military authorities, to make known to the world as soon as possible the contributions that we made to scientific knowledge during our war effort?

(2) With special reference to the war of science against disease, what can be done today to organize a program in order to continue in the future the work done in medicine and related sciences?

(3) What can the government do today and in the future to support the research activities undertaken by public and private organizations?

(4) Can an effective program be proposed to discover and develop the scientific talent of American youth, so that it is possible to ensure the future continuity of scientific research in this country, at a level comparable to that achieved during the war? “179 .

With this script, Bush focused on the natural sciences, including biology and medicine. The techno-scientific revolution began in the field of physical-natural sciences, taking many decades to reach the social and human sciences. The central thesis of his report was expressed in his letter of reference, as well as in numerous passages of the text:

“Scientific progress is an essential key to our security as a nation, to improve our health, have higher quality jobs, raise our standard of living and progress culturally” 180.

It is well understood that, when Bush talks about scientific progress, he refers above all to what is now called basic research in the field of physical-natural sciences. The second guiding idea, possibly the most novel one, was to affirm that “science can only be effective for the national welfare as a member of a team, whether in conditions of peace or war” 181. It was consecrated at the theoretical what was being the usual practice in the US during the military conflict: the scientists worked closely with engineers, military, businessmen and politicians in their research, leaving the traditional ivory tower of academic science. Bush’s first postulate has been criticized from several points of view, as we will see later. However, almost nobody has dealt with the second. In our view, this “teamwork” has contributed powerfully to modify scientific activity. The daily mestizaje between the diverse subcultures that conform the macroscience and the technoscience modified the habits, the customs and, in part, the values.

Bush affirmed with great energy that the American traditions in science and technology were insufficient to maintain the leadership that the USA had shown throughout the war. Taking medicine as an example, he pointed out that:

“The traditional sources of support for medical research, largely income from donations, grants and private contributions, are decreasing and there is no immediate prospect of a change in this trend. In the meantime, the cost of medical research has risen. If we intend to maintain in medicine the progress that marked the last 25 years, the government should extend its financial support to basic medical research in medical schools and universities “182.

This will be the main answer to Roosevelt’s four questions. The important thing is that the Federal Government leads scientific research providing important budgets. During the war it had been like this, but only in the areas that interested the Department of Defense. It was necessary to extend this new financial structure to all the physical-natural sciences. Said in our own terms: Bush proposed that the government become the main techno-scientific agent of the country. This was the case in the era of macro-science. The Government and Congress created scientific policy commissions and reserved a budget chapter to encourage research and development. It was about deeply involving the executive and legislative branches in the promotion of scientific research. This political-financial turn was Bush’s central proposal to Roosevelt. For our part, we consider it as the first major structural change, imitated by other countries.

Turning to the defense chapter, Bush pointed out that modern warfare was “a combat of scientific techniques”, giving as an example the battles against German submarines, radar and other newly developed weapons. The defense and attack capacity of a nation depends strictly on scientific knowledge. Therefore, he concluded, “there must be more – and more adequate – military research in times of peace” 183. Civil scientists had to continue collaborating with the military:

“The best way to achieve this is through a civilian control organization with close ties to the army and the army, but with direct financing from Congress and explicit powers to initiate military investigations that will complement and strengthen those carried out directly under the control of both forces “184.

The armies would maintain their own research centers, but also proposed to create an organization that would institutionally link the scientists and the military, always under the financial dependence of the Congress, that is, with a specific chapter of the state budget. Bush again insisted that the Government and Congress had to be the main techno-scientific agents, notwithstanding the fact that military agencies dedicated to research still existed.

The design of the new science and technology system was completed with the industrial chapter. For there to be full employment – reasoned Bush – “we must make new products, better and cheaper”. For that, there should be:

“A multitude of new and vigorous companies. But the new products and processes are not fully developed. They are based on new principles and new conceptions, which in turn result from basic scientific research. This is the scientific capital. On the other hand, we can no longer depend on Europe as an important source of this capital. It is evident, then, that more and better scientific research is an essential element for achieving our goal of full employment “185.

The syllogism is forceful and is at the basis of what has subsequently been a linear model of science and social progress. Full employment and the progress of a society can not be achieved without competitive companies. These are not competitive if they are not able to manufacture and sell new and cheap products. Commercial and industrial innovations will only arise if there are technological developments and scientific advances. Therefore, scientific research is the basis for business progress and full employment, just as it was for health and defense. We could criticize more than one of these inferences, but our objective in this section is not criticism, but analysis. We will see that the Bush model is underlain by other postulates, which should be elucidated before proceeding to a critical comment. It is obvious that Bush assumes a market economy and defends a position of economic liberalism. However, there are other budgets that are even more decisive, as we shall see below.

What is remarkable is that Bush speaks of basic scientific research as a new form of capital, scientific capital (or knowledge, as it would now be said). Until the Second World War, the US imported scientific knowledge from Europe and then implemented it technologically, industrially and commercially. After the tremendous war, Europe was going to be decapitalized from the point of view of knowledge. Many of its scientists would die or emigrate, the industry would be devastated and there would be no sources of funding to promote basic research, since European countries would have other priorities, such as the reconstruction of citizen and industrial infrastructures. Therefore, it was essential that the US take over and take control of this new capital market. In fact, he was already doing it, by hiring the best European scientists in their emigration service. The aim was to reaffirm an existing practice, consolidating it for the future as a general strategy. Generally speaking, it can be said that one of the great successes of the US in the twentieth century has been its ability to attract intellectual capital to the country, coming first from Europe, then from other countries. Nowadays, that policy is maintained. The USSR also practiced it but, after its disappearance as a State, the scientific capital market is almost completely dominated by the US, despite the efforts of Canada, Europe and other countries to attract “brains”, as they say.

We are only commenting on the summary that Bush himself made of his report, knowing without a doubt that a president was not going to read the entire text, but the summary. There are, very clearly synthesized, the driving ideas of the scientific policy that Bush proposed to create. The basic pivot is always scientific research, based on a very important and highly innovative reason for the time, at least at those levels of interlocution. Money, natural resources and industries are important forms of capital, but there is a new one that has been cultivated in Europe and not in the US: science. Assuming the risk of incurring an anachronism, we will say that Bush anticipated some of the basic theses of what is now called the knowledge society, understood as a new form of wealth and power:

“How do we increase this scientific capital? In the first place, we must count on many men and women trained in science, because the creation of new knowledge as well as its application to practical purposes depends on them. Second, we must strengthen the basic research centers that are mainly faculties, universities and research institutes “…” Only they devote almost all their efforts to expanding the frontiers of knowledge “186.

Apart from the industrial factories, we must be aware of other types of factories, those that generate knowledge and expand the borders of the noosphere, to put it in terms of Sáez Vacas 187. These are the scientists, with their faculties, universities and research centers. investigation. Investing in science means increasing the noocapital, provided that these investments are directed by competent people in the field. The Scientific Council proposed by Bush was a kind of Board of Directors of scientific capital, which, with government funding, had as its main task to accumulate and increase the new form of capital. In our view, here lies the great theoretical change that underlies, with relative clarity, the Bush report. Scientific knowledge is no longer a good in itself, but an economic good, and in particular a capital. Some commentators have claimed that this terminology was purely metaphorical and that it had been introduced taking into account the possible readers of the report. That rhetorical ability is true. But it is no less true that, in affirming these ideas, Bush was prefiguring one of the most important distinctive features of the techno-scientific revolution: the conversion of scientific knowledge into economic capital and of scientific communities into techno-scientific enterprises. Obviously, he did not take this last step. He limited himself to advocating the close link between academic science and the business world, as indeed occurred in the US during the era of macro-science. But it should be emphasized that Bush anticipated in 1945 one of the basic tenets of current technoscience, which clearly distinguishes it from modern science: knowledge is an economic (and military, and social, and sanitary) good, not just an epistemic good. In our view, this is the main postulate of the Bush theory and the techno-scientific revolution. That is why we affirm that technoscience implies a radical change of the values of science, starting with its main value, scientific knowledge.

Bush also indicated the possibility of promoting scientific research in companies through an adequate tax and patent policy, actions that were put into practice forty years later by the Reagan administration and that, in our opinion, were decisive in the emergence of the technoscience proper, which is based on the privatization of noocapitals and their subsequent profitability through patents, licenses for use, knowledge transfers, stock investments, the sale of techno-scientific companies, etc. Being a staunch supporter of the government’s primacy as a techno-scientific agent, Bush advised “to create a permanent advisory board on science, to advise the executive branch and the legislature on these matters.” 188. On our own terms, political power should to be the main manager of the new capital, scientific knowledge, promoting its creation and its transfer to companies, hospitals, the military sector and, ultimately, society. Although he did not develop the thesis that science greatly increases the cultural level of a country, there is no doubt that it depended on the promotion of science education among young Americans. The launching of a powerful action to grant scholarships for research personnel and the organization of a system of dissemination of scientific knowledge, apart from the classical academic journals, were two other proposals of Bush, in response to the fourth question of Roosevelt:

“The speed or slowness with which we move any scientific frontier will depend on the number of highly qualified and trained scientists who explore it” 189.

And a little later:

“The real ceiling of our productivity of new scientific knowledge and its application in the war against disease and the development of new products and industries, is the available number of trained scientists” 190.

Note that the ultimate goal always consists of expanding the frontiers of knowledge. This is the new form of capital. To increase it, it is necessary to train scientific researchers through scholarships, so that the source of knowledge does not run out. People are those who generate new knowledge, provided they have a good previous training and adequate tools. To the extent that said capital grows in a country, it will be more militarily powerful, healthier, more productive and more cultured, apart from approaching the goal of full employment. The endless border that gave title to the report is the new frontier of knowledge, which the US had to conquer. The project had enough time to serve as the basis for a lasting scientific policy, as it has been, with the logical ups and downs and changes in orientation. The research and development programs promoted by the US government have been changing according to the needs and ideologies of the successive administrations, but the basic structure of the system has remained intact, at least until the mid-1960s.

There would be many more things to comment on in the Bush report, but the ones above are enough for our purpose in this book. We are no longer dealing with specific macro-scientific initiatives like those of the 1930s at Stanford, MIT or Berkeley, some of them with the participation of Vannevar Bush himself. We are faced with a theory of scientific practice, and even more, with the foundations of a new political economy of science. Economically it is inspired by capitalism. Politically in the democracy and in the belief that the political power must lead the conquest of the new frontier of knowledge, because it will bring benefits for the whole country. On the other hand, it is a clearly nationalist theory, or if you prefer Americanist. For Bush it is clear that the US must take over from Europe in the cultivation of scientific knowledge and that it must do better than the Old Continent, closely linking basic research and technological development. The SCyT system is designed as a system created by the USA, for the USA and in the USA. The brief paragraphs that Bush devotes in his report to the international diffusion of scientific knowledge accumulated throughout the war are the weakest in the entire report. Until the 70s there was no scientific policy with international objectives. It is the phase of technoscience, in which the transfer of knowledge and technology to other countries became an instrument for diplomacy and the signing of agreements of interest to American companies.

From the axiological point of view, there is also a central postulate: the freedom of investigation. Bush insists on her again and again throughout the text. He stressed that “internal control of policies, personnel and the method and scope of research in the hands of the institutions in which it is carried out should be left” 191. These institutions were universities and research centers, which Bush considered as “the springs of knowledge” 192. During the war had to impose rigid controls on the production of knowledge, but once the military conflict was over had to return to full investigative freedom. Bush made a true song to the freedom of investigation when affirming that:

“Scientific progress on a broad front results from the free play of free intellects, who work on issues of their own choosing, and according to the way their curiosity about the exploration of the unknown dictates. In any government support plan for science, the freedom of investigation must be preserved “193.

This was the most controversial point of his report at the time of passing it to the approval of the North American Congress. According to Bush, each researcher should be free to choose their own research topics. This contradicted the recent practice, in which the Directors of the macroprograms strictly defined the objectives and programming, as we saw at the end of the second chapter. On the other hand, many parliamentarians believe that the funds that the Congress devoted to research should be subject to the same legal and procedural rules as the rest of the public investments, something that Bush tried to avoid as far as possible, attributing the responsibility of the management to the addresses of the federal agencies and, through them, to the North American Government. It is not easy to foresee in detail the expenses that will arise when developing a research macro project. The scientific discoveries and technological advances that may occur modify the financial needs again and again, normally upwards. That is why Bush wanted science to have the least legal and political obstacles. The conflict between the freedom of research and the social control of science is at the origin of technoscience. Throughout the twentieth century it manifested again and again, especially in the crisis of the 1960s. Bush tried to make the relations between science and society the traditional ones: let the experts do it. However, he affirmed at the same time that the Congress and the Government had to become the main driving agents of the investigation. How will not finance the research, unless it acts for philanthropic reasons, as a patron? The congressmen, the military and the businessmen always tried to impose their own criteria and priorities, contrary to the autonomy of the science that Bush claimed. The tension between freedom and control is one of the conflicts of values typical of technoscience.

IV.4: New techno-scientific agents.

We will dispense with the historical details of the constitution of the North American system of science and technology to analyze its basic structure, as it was configured at the time when technoscience appeared, that is to say at the beginning of the 1980s (see table 1). We can distinguish six main areas of action, with different agents in each of them.

(a): The White House had its Scientific Council, as Bush had advocated in 1945. In addition, the Executive Office of the President had its own scientific-technological policy office, linked to the National Academy of Sciences and Congress. Both the Senate and the House of Representatives had their S & T Committees, usually with the presence of scientists and engineers, apart from the politicians themselves. In addition, the Congress had the famous Library of Congress, an Office of Evaluation of Technologies and another Office that was in charge of Accounting Control. The Patent Office, created years before, traditionally depended on the Department of Commerce, which had been one of the most active in the 1930s when it came to financing scientific research. We can summarize the structure of this first area of the SCyT system by saying that there is an alliance, not without problems, between the executive power, the legislative power and the emerging power of scientists and engineers. There would not have been macro-science in the postwar period without the insertion of prominent scientists at the heart of executive and legislative power. Obviously, this politicized science. Maintaining the axiological neutrality of science from the Second World War is a remarkable ingenuity. Interestingly, it is the time when many philosophers and scientists insist on the strict separation between science and values.

(b): The Federal Agencies dedicated to science and technology were many. Each one of them was in charge of some great programs, although there were also conflicts between them, such as the Genome project. The NSF, NASA, the Environmental Protection Agency, the Institutes of Health and the agencies of the Departments of Defense, Trade, Energy, Agriculture, Labor, etc. stood out. All these federal agencies maintained close collaborative relationships with universities, governmental research centers, independent research centers and, of course, industries, with their laboratories and their R & D departments. The Patent Office began to resemble a knowledge bank, at least with regard to R & D. The Library of Congress played a similar role in terms of traditional scientific knowledge. The private foundations completed the map of the North American S & T system, contributing to the financing of specific programs, to the incorporation into the system of outstanding scientists or to the provision of large equipment. This was the basic map of the second level of the North American S & T system. Of course, some of these institutions and corporations also brought together complex structures. These include the management departments and the advisory committees. Scientists and engineers began to compete with each other for having a place in these commissions and decision instances, not only for making discoveries in the laboratories and publishing them quickly in the most prestigious journals.

(c): The military organizations dedicated to R & D continued to exist after the war and its growth was continued, except in the decade 1965-75. It should be noted that since the 1980s their budgets have increased rapidly, so that the militarized technoscience forms a third sector of the North American SCyT system. This third area is apparently separate from the others, especially the market and society, but in fact maintains very close links with many civil and industrial techno-scientific agents. A reflection on technoscience and on techno-scientific systems that does not take into account the technical-military sector is clearly insufficient. Specifying its internal structure is not usually easy, due to lack of public information. However, there are enough case studies to analyze military technosciences.

(d): A fourth area is the business itself. At first it was strictly industrial. In the last quarter of the century it was evolving towards the economy of information and knowledge. Until the 60s, it intervened complementing the initiatives of the government and federal agencies, as well as signing research contracts with universities and research centers, as in the industrial era. From the 80s, techno-scientific companies began to be the protagonists in research, designing their own R & D policies. The State continued to play an important role in the SCyT system, but rather as a catalyst rather than as an engine, with the exception of some macroprograms, which continued to be the responsibility of federal scientific institutions. At this time two major developments occurred in this area of the SCyT system: the emergence of new sources of funding (venture capital entities, stock exchange, etc.) and the incorporation of some scientists to the Boards of Directors of these companies, with the consequent conflicts of interest. In section II.3 we had the opportunity to comment on these changes.

(e): The fifth area of the SCyT system is the market, in which techno-scientific innovations conveniently redesigned for civilian use are marketed. This is the case of radars, computers, telecontrol systems, robotics, synthetic fibers, polymers and some commonly used devices, such as television, telephone, microwave or aircraft. From that moment, the acceptance by consumers of new techno-scientific inventions becomes a decisive criterion for the evaluation of techno-scientific actions. Research and development are not enough, it is also necessary to consider innovation. The design of the S & T policies of private companies not only includes scientific and technological aspects, but also financial and mercantile ones. In the end, you have to sell the knowledge, it is not enough to produce it. This is the era in which macro science is giving way to technoscience proper, which is characterized by the greater role of private initiative. Knowledge is not only a capital, but also a commodity in the market. There began to be large private deposits of knowledge, not just public deposits such as libraries and patent offices. Overall, since the 1980s this fourth area of the SCyT system began to be the main one. That is why we speak of a systematic privatization of knowledge, which breaks with the traditions of modern science.

(f): The sixth and last area that we are going to distinguish is society. Traditionally, the relationships between science and society had been channeled through educational systems, and in particular through universities and their teaching and transmitting knowledge function. We already saw that Bush recommended reinforcing institutions of higher education, which was done. American universities became the best in the world in the post-war period. It also supported the dissemination of scientific knowledge in society, which was also carried out, although through new communication channels, which are specific to technoscience. It is the moment in which large platforms emerge to present the techno-scientific novelties (Nature, Science, etc.) as well as magazines, magazines and supplements of quality disclosure. Cinema and science fiction literature also played an important role throughout the 20th century.

As a whole, the traditional educational system was superimposed on a second system to disseminate knowledge, based on the new means of information and communication. From the 80s, the presentation of the great scientific and technological advances through the mass media became a new techno-scientific practice. Apart from the great researchers, good disseminators and communicators of techno-scientific knowledge began to be appreciated. It is a new structural change, which replaces the presentations of scientific advances with notable people, typical of modern science, by media campaigns to launch such novelties, in order to quickly reach the whole of society. Scientific and technological knowledge is disseminated more and better, but society is conceived as a passive entity, that is, as a simple receptor of information and knowledge. We have already seen in chapter 2 that, since the mid-1960s, society had abandoned that passivity and began to be critical of some aspects of the SCyT system, beginning with its dependence on military organizations, and continuing with the environmental impacts produced by some innovations. techno-scientific Since then, it can be said that the conflicts between technoscience and society are part of the structure of SCyT systems.

This first sketch of the basic structure of the North American system of science and technology shows the profound transformation that took place after the war, following the master lines of Vannevar Bush’s plan. The scientific-technological research was strongly promoted by the Government and the Congress through the federal agencies, most of which had very considerable budgets to develop their R & D activities. Subsidiarily, many other agents collaborated with this scientific policy. This new design of the SCyT system led to profound changes in scientific practice, among which we will mention the following:

1.- Very considerable budgetary allocations for R & D. Federal support grew by 14% per year in constant dollars between 1953 and 1961. As Bruce LR Smith points out, “growth was both a condition and a part of the doctrine,” 194 as it allowed discrepant scientists to silence and favor to the enthusiasts. Budgetary policy is a basic component of S & T systems, both for the Government and the Congress and the Federal Agencies.

2.- Creation of Commissions for the design of scientific policies and for decision-making in Congress. This new techno-scientific agent, the Advisory Commissions, is of enormous importance in the new SCyT systems. Their functions can be very diverse, depending on the institutions or companies they advise, but they always meet three: guarantee the presence of scientific communities in decision making, propose new initiatives and resolve conflicts that may arise between different agents of the system SCyT. The presence in these Commissions entails power. The struggles to access them are commonplace, and not only between research lines that compete with each other, but also between scientific disciplines.

3.- Promotion, financing and development of strategic projects from the National Science Foundation and other Federal Agencies. This began the tradition of priority research lines, which has deeply marked the structure of techno-scientific activity. Like the Government and the Congress, the various Federal Agencies defined their objectives, indicated and financed their priority lines and developed specific programs to achieve those objectives. Through these actions there was a strong interrelation between the scientific and engineering communities and the new agents of the S & T system. In addition, the initial conditions that would later make scientific-technological advances possible were created. In the age of technoscience, the greatest advances in knowledge occur in those areas that have previously been chosen as priorities. We are facing a progress directed, and even planned, with the peculiarity that the direction does not always correspond to the scientists. As we saw in chapter 2, those scientists who assume these functions experience a mutation as scientists. The scientist-manager brings a new form of scientific subculture.

4.- Promotion of projects and research contracts, making the research teams compete at the federal, not state, level. This forced the scientists to make a previous design of what they wanted to do (state of the matter to be investigated, starting hypothesis, objectives to be achieved, deadline for this, human and economic resources needed, methodology to be applied, work plan, results expected scientific and technological, etc.). The Universities and Public and Private Research Centers that wanted to advance in science or technology had to adapt to the Government’s policies or make proposals that would be interesting for the NSF and the other Agencies. Not without rejections, research became heavily mediated by scientific-technological policies. In addition, there was a standardization of how to make research proposals, generating protocols and forms that represent authentic symbolic generalizations of techno-scientific practice. Instead of proposing hypotheses, theories, etc., the scientists have had to first propose research projects, some of which are acceptable to the Agencies, others not. Mastering these new forms, which are not mathematical or conceptual, but practical, became a new requirement for scientists. With the advent of technoscience, all these formats have been computerized and telematized. A significant part of the researchers’ work time is currently dedicated to completing these forms. From the point of view of modern science, it may seem a minor work, compared to the excellence of work in the laboratory. 

However, to be techno-scientific you have to be an expert in these new symbolic generalizations, which are as important as traditional scientific languages. In fact, the evaluations of the applications are carried out in the first place for reasons of form (having completed the templates well). Only when this threshold has been passed do questions of scientific content begin to be analyzed.

5.- Creation of new professions, such as advisors and experts in scientific policy management, as well as in the evaluation of science and technology, recycling some scientists and engineers. The weight of these new techno-scientific agents grew as the techno-scientific system consolidated, giving rise to the dreaded macro-science bureaucracy. Today, technoscience has generated an immense info-bureaucracy. The multiple WEB pages are a new scenario of techno-scientific activity, as it happens in other sectors of social life.

7.- Extension to the research projects of the anonymous and peer evaluation system, traditional in the scientific communities to publish in the journals. The creation of Agencies for the evaluation and follow-up of research led to a revolutionary change in terms of scientific practice, as the evaluation processes became standardized and formalized. But more important still is the change in the structure of evaluation committees, especially in private techno-scientific companies. In this case, the evaluation criteria are never only epistemic. The axiological plurality of science is manifested empirically in the various evaluation protocols used to make decisions, choose among alternative proposals, allocate funds, hire people, establish categories within the research staff, etc. Technoscience has not only modified the context of research and application, but also that of evaluation.

8.- Promotion of patents and the transfer of knowledge to industry, always through economic incentives. Roosevelt’s question to Bush about how to publicly disseminate the secret knowledge that had occurred throughout the war pointed to a central theme of technoscience: the dissemination and dissemination of scientific knowledge.

We could continue to enumerate specific changes in techno-scientific practice, especially if, apart from the public sector, we dealt with the private sector of R & D, but the previous seven are more than enough to give us an idea of the profound differences between technoscience and science. traditional science Of course, we do not intend to claim that the seven previous points come directly from Vannevar Bush’s report. Nor that there were no precedents for this type of action 195. What we try to characterize are the differences between concrete techno-scientific systems and academic science prior to the Second World War. This plurality of subsystems was gradually established and consolidated during the second half of the twentieth century, but here we are not so interested in the steps that were taken for this, but the joint structural change. Today, SCyT systems, with all the subsystems imbedded in them, are consolidated in many countries. Although they always evolve and change, they maintain a series of invariants that allow them to be characterized with a certain degree of precision. In any case, there is no doubt that the current SCyT systems show very important structural differences when compared with the scientific institutions of the modern era. Then there was an academic science. Nowadays it is possible to affirm that we are before a post-academic science, as Ziman says 196, although this denomination does not seem to us the most successful to understand the background of the transformations that have taken place throughout the 20th century.

IV.5: Bush’s linear model as a theory of science.

Given these details, let’s return to the Bush report, since it not only provides a series of proposals for action to transform the S & T system, but also a theory of science, which has been called the linear model. It is not a philosophical theory, because it does not focus on scientific knowledge, but on the social function of science, and more specifically on basic research. The Bush theory has served as the basis for the new scientific policy and the changes in the structure of scientific activity that were made throughout the 20th century and that we have just enumerated and commented very succinctly. Technoscience has not had a logical, epistemological or methodological foundation, as many philosophers tried to give to science throughout the 21st century. Its justification has been praxeological, or if you want pragmatic, and more specifically economic, political and military, which is a new difference between technoscience and science, of great significance for philosophy.

The Bush theory can be criticized from many points of view. It is not a rigorous theory, nor precise. Nor is it appropriate to the data offered by the history of the relationship between science and technology. As many authors have stressed, it is not true that basic research always generates technological development. Very often the opposite happens: technology comes first, and then scientific theories come. But the truth is that the Bush theory has been useful and effective, since it has contributed considerably to transform the world, in this case the science and technology system itself. It is a technological theory, not a scientific theory. It’s social engineering, to put it in terms of Popper. Despite all its inadequacies, it remains operational and effective, since many scientists, technologists and experts in scientific politics continue to accept it as if it were enunciating the fundamental “laws” of techno-scientific practice. The criticisms and “refutations” of historians, philosophers and sociologists have had very little effect on the theory, and this for reasons that can be easily understood: they have not been made from the techno-scientific paradigm itself and therefore have not even been addressed. Neither have provided alternatives, so, in general, have been ineffective, as well as uncomfortable. The “Sokal affair” and the recent “wars of science” show the rejection of the hard core of technoscience with regard to this type of criticism, which is made from the periphery of the system, if not from the outside. From an argumentative point of view, the scientific ignorance of the critics is insisted on. But the function of these debates is to reinforce the basic structure of the SCyT system and renew its fundamental postulates, which have their origin in the report by Vannevar Bush.

We saw that Bush advocated a new independence from Europe, not political, but scientific 197. The very title of his report, the endless border, touched the foundational fiber of the US of America. Science was the new gold mine, where the foundation of economic capital and the basis of military, sanitary and commercial progress can be found. As he explained his thesis, he was proposing a strategy of political-scientific action with clear nationalist connotations:

“Today is more true than ever that basic research is the one that marks the step to progress. During the nineteenth century, the naive mechanical talent of the Yankees, based mainly on the basic discoveries of European scientists, made the technical arts advance a lot. Now the situation is different. A nation that depends on the others in its new scientific knowledge will be slower in its industrial progress and weaker in its competitive position in world trade, regardless of the mechanical abilities it possesses “198.

The good situation of the US in terms of technology was not enough. It was required to go to the very core of technological, economic and military progress, which lies in scientific knowledge, which is only obtained by promoting basic research. This becomes the main economic engine. We are facing what we can call the basic tenets of techno-scientific activity, or if you want the first formulation of the metaphysical commitments of the techno-scientific paradigm, to use Kuhn’s terminology. Note that laws of nature are not being formulated, even if they are invoked. Unlike Newton, Bush is enunciating the metaphysical principles of a new social philosophy, not a natural philosophy. These principles have become models (in the sense of Kuhn) of the progress of a society, and not only heuristic, but ontological. We have verified that the techno-scientific revolution generated new symbolic generalizations (indicators, scientometrics, impact indexes, quantitative studies on science and technology, etc.) and also gave rise to exemplary actions (foundation of the NSF, establishment of a competitive system for obtaining funds for research, the creation of techno-scientific companies, etc.), subsequently imitated in the successive countries that were adhering to the new paradigm. Many of the components of the techno-scientific paradigm, at least in relation to its first epoch, that of macro-science, have their expression in the Bush report, and for that reason we consider that text as the first theoretical expression of the techno-scientific revolution.

Although Bush alludes again and again to scientific knowledge, the “principles” he enunciates and the consequences or laws that derive from them are all related to scientific-technological activity. Bush is not analyzing the structure of the physical, chemical or biological world, but that of a very specific sector of social life: science. The practical principles he enunciated (his social metaphysics) generate laws, but not laws of nature, but laws for society (budgetary, fiscal, economic), which had to be approved by Congress and the Senate and put into practice by the Government and its Agencies. As we have insisted throughout this book, technoscience does not pretend to dominate or transform nature, but society. Bush has no doubt that knowledge of the laws of nature and basic research are the most appropriate instruments to transform and improve society, understanding as such the American society. His social metaphysics focuses on this thesis. From it emanate their recommendations and proposals, always with a view to two objectives:

1.- The predominance of the US over others, both in terms of military power and industry and trade. This primacy had been achieved in the war. It had to be consolidated in the post-war period.

2.- The health and the internal economic progress of the country.

Bush does not advocate knowledge for knowledge, nor the search for truth. These are not the objectives of technoscience, but instrumental means to achieve the new objectives. Nor is he a follower of the Baconian program: knowing nature in order to master it better. The technoscience that it institutes and theoretically bases has other ontological commitments and, of course, other objectives. Half a century later, when the techno-scientific revolution has triumphed and spread through other countries, although US dominance remains clear, it can be said that these objectives have been achieved, especially the first, which was the main one. We are not saying that the victory of the US in the Cold War against the USSR and its current scientific, technological, military, political, industrial and commercial hegemony is a direct effect of the solid establishment of the techno-scientific revolution in that country. of the Second World War. This is just one of the factors that have influenced the change of power relations worldwide, but it is certainly one, and very important. The important thing is to be clear that the objectives of the Bush action are about power and practice, not about nature and knowledge. For technoscience, scientific knowledge is a means, not an end. This is one of the basic differences between technoscience and science.

The Bush action was based on a theory, which we will now analyze in more detail. It is usually called a linear model, and we have already mentioned that it has received multiple criticisms. For our part, we could also express our total disagreement with this model, which does not correspond to reality, but with it we would achieve nothing, except to satisfy our good conscience. Therefore, our perspective is different. In the first place, we are interested in analyzing the main postulates of this theory. In the second place, we intend to show that there are non-explicit postulates, or if they prefer to be hidden, and that they are determinants for the further development of techno-science and the scientific-technological policies that have driven this development.

In the studies on science and technology, various schemes have been proposed to synthesize the general structure of the Bush report, based on which the techno-scientific system was built in the United States. One, which fits well with the text of the report, insists on its socio-economic aspect and distinguishes six links:

Basic Research -> Applied Research -> Technological Development -> Productive Development -> Economic Competitiveness -> Social Progress 199.

It is important to note that Bush’s original theory was this. Social progress depends on the creation of jobs, business and trade, which in turn depend on the invention of new products and therefore on technological innovations, which only arise if there is applied scientific research and, as a foundation of it, basic research. These are the initial postulates.

Another of the proposed schematizations to reconstruct the linear model is made from a more technological perspective. It adds an important facet, on which we will return later, the use of technological products:

Basic Research  Applied Research  Technological Development  Product Development  Production  Use 200.

In our view, we can introduce some improvements in both schematizations to collect more aspects, on the one hand distinguishing other links in the chain, on the other introducing additional lines of chaining. From the outset, we will replace the term “product development” with the term “innovation”, nowadays more common. Innovation means a technological development that is going to be launched on the market. Therefore, it incorporates other factors, such as financing and marketing. Also, between the production and the use it is convenient to introduce intermediate stages, namely, the distribution and sale of the product. In order not to complicate the scheme much, we will summarize these phases by means of the term “commercialization”. On the other hand, it is assumed that the use of technological products satisfies the needs of people and generates well-being, one of the basic components of social progress. Therefore, we will choose to combine both schemes and use the following linear model as a starting point:

Basic research  Applied Research  Technological Development  Innovation  Production  Marketing  Use (or consumption)  Social Progress.

This would be the general scheme underlying the Bush report. However, Roosevelt asked him specific questions, and one of them referred to the relationship between science and military institutions. In this case we would have a quite different scheme:

Basic research  Applied Research  Technological Development  Innovation  Production  Weapon capacity  Use (or dissuasion)  Military power.

Well understood that, apart from those who use techno-scientific weapons, there are those who suffer its effects, namely the victims. This type of “users” must also be taken into account, since military techno-scientific actions can produce goods for some, but they certainly generate evil for others.

A third variant of the scheme represents the impact of science on business activity, an issue explicitly considered by Bush in his report and central to our inquiry into technoscience:

Basic Research  Applied Research  Technological Development  Innovation  Business Competitiveness  Production  Marketing  Consumption  Economic Benefits

A fourth referred to health, and Bush’s proposal can be summarized as follows: Basic research  Applied Research  Technological Development 

Innovation  Production  Clinical use  Health.

We could propose other specific lines, both from the Bush text and from further developments in American science policy, for example in relation to the environment. Overall, more than linear, we are facing an arborescent model, where basic scientific research is always at the root and technology constitutes the trunk. The branches of the tree are some social sectors (society in general, defense, industry, health, etc.) which are directly influenced by techno-scientific innovations, and therefore the basic research that sustains them. It should be emphasized that all ramifications are based on scientific research and technological innovation. One more reason to talk about technoscience. It should also be noted, as far as the axiology is concerned, that the assessments that can be made of techno-scientific actions depends very much on the place where the evaluator is located. For example, if he is the one who suffers a military action or who is injured by a medical intervention, his assessment of technoscience will be highly negative, as is logical. We will conclude from this that technoscience is not perceived (or valued) equally from one place in the structure of the science and technology system than from another. This does not imply a relativism, but a structural perspectivism. Since there are different structural components, the assessments made will be coherent with the place of the system from which they are carried out. Therefore, dissensions and value conflicts are guaranteed in technoscience.

These early schematizations, although incorporating more analytical nuances, have two important drawbacks. In the first place, they do not represent the role of the Administration and its scientific policies to set the system in motion. Therefore, new components must be incorporated:

Departments of Technoscientific Policy  Parliament (budgets, laws, control)  Government (actions of techno-scientific policy, Agencies, appointments)  Financing  Basic research  Applied Research  Technological Development  Innovation  Transformation (of armies, companies, industry health, societies, etc.).

In our view, this last outline makes explicit the important role of governments in the techno-scientific development, through their scientific-technological policy services, during the first epoch of technoscience. It also synthesizes the last links of the previous models in the general concept of transformation of the world, which seems key to us to talk about technoscience. These transformations can be positive or negative, of course.

But, secondly, we must not forget that at the stage of technoscience itself, another type of agent emerged, the techno-scientific company, which tends to replace government as the engine of the SCyT system, except in the case of scientific macroprojects. It is the moment when large multinational companies are emerging that design and implement private scientific policies, as well as small companies that do the same. In such cases the scheme is still valid, but small changes have to be made:\

Departments of Techno-Scientific Policy  Board of Directors  Scientific Management  Financing  Applied Research  Technological Development  Innovation  Commercialization  Economic benefits.

The main novelty is the disappearance of basic research (although some funds can be devoted to it) and the prioritization of applied research and innovation. Assuming that governments assume the task of encouraging basic research and that the results of the same are made public, private techno-scientific policies prioritize technological innovation and the market, while privatizing techno-scientific knowledge. It should not be forgotten that since the 1980s private financing in R & D exceeds public financing, at least in the US. That is why we say that the appearance of this new motive agent of technoscience characterizes the second epoch of technoscience, nowadays in full expansion.

So far the first formal improvements that could be made to the linear model. In all of them there is a constant component: financing. Basic research requires financing, be it public or private. Without economic resources to enhance it, the machinery does not start up and science does not generate the social benefits (military, business, etc.) that Bush assumes. Therefore, the financing structure of scientific research is decisive when analyzing an SCyT system. A technoscience financed exclusively by the State, as in the USSR, is not the same, a technoscience financed 50% by the State and companies, as in the US in the 1980s, or a technoscience financed at 50% by companies and 50% on the Exchange. This last financing structure is the most typical of American technoscience at the end of the century, while macro-science is distinguished by basically state funding.

Leaving aside budgets and ideological criticism, there is another important formal flaw in the Bush model: the linearity itself or chaining of the various components. The model improves if we consider it as arborescent and introduce new components, but even so its linearity does not correspond to real techno-scientific practice. It happens rather that many of the components that we have distinguished and sequenced affect each other. For example: users are a continuous source of innovation, especially in the field of technology; From the society emerge new lines of scientific policy action, for example from environmental groups and NGOs. Although it is represented linearly, the model is more complex. It would be necessary to opt for models in which the various components influence each other, although in varying degrees and with asymmetries. A possible scheme would be the following:

Scheme 2

We distinguish several relevant sectors in a SCyT system such as the North American: the political, the financial, the scientific-technological, the business, the legal, the military, the market and society. The flows and interactions can occur between all of them, although the greater or lesser relevance of one or the other flow arrows allows to distinguish between different types of S & T systems. For example, in the era of macro-science, the main flow comes from governments and their agencies. On the other hand, in technoscience, private companies and financial entities are the ones that take the most prominence. Within each of these sectors there may be different relevant agents, so it would be necessary to analyze the structure of said agents in each country, in each discipline and in each historical moment. From our point of view, it is fundamental to include society among technoscientific agents, not only because ultimately the majority of actions are directed to it, but also because society is not passive with respect to technoscience. In a representative democracy, it may prefer one or the other politicians (rulers, parliamentarians) depending on their respective scientific policies. It can also generate NGOs that criticize and influence in part on technoscience. The democratization of science would mean a greater flow from society to the instances where decisions are made about technoscience. Finally, in society are the end users of techno-scientific products, whose valuations and innovations of use are of great importance for an advanced S & T system.

This model does not correspond to Bush’s conceptions but tries to correct some of its defects. Here we will limit ourselves to propose it, without developing it and without showing its potentialities to represent schematically some of the great changes of the techno-scientific system after the crisis of the Bush model from the 70s and the advance of the techno-scientific companies, based on a new contraro social science, as we saw in chapter 2. A more refined analysis would allow us to distinguish additional sectors. In chapter 5 we will propose some improvements, although only in the field of values. We presuppose that the different technoscientific agents have their own value systems, so the interactions between them involve a certain axiological miscegenation. The value system of technoscience is composed of several subsystems of values that are not hierarchical to each other, at least in principle. De facto, there is always some subsystem of values (military, business, political) that prevails over others.

In any case, we deny that basic research is the engine that draws the other nodes of the system. In some cases it can happen like that, but generally not. There are occasions, like the Second World War, in which the main engine of the system are military institutions. In other occasions they are the companies, or the politicians, or even the jurists. Legal reform such as the liberalization of a patent system can have an impact on the entire SCyT system. Scheme 2 is purely formal and should be implemented in each specific case, pondering the greater or lesser influence of each of its components. The interesting thing is to analyze the changes in structure experienced by technoscience throughout the 20th century, as well as to propose new structural changes in current technoscience. We will not get to much in this work, but at least we will take some steps in that direction.

IV.6: Plurality of techno-scientific agents.

The investigation of the new framework for techno-scientific activity has shown us many things, among them the existence of new agents and new types of actions in technoscience. Classical scientific actions were reduced to observe, measure, experiment, demonstrate, formulate conjectures, contrast them empirically and theorize, and then publish, disseminate, apply, teach, etc. According to the distinction between the context of discovery and the context of justification, the philosophy of twentieth-century science was exclusively interested in the results of such actions, that is, in observations, measurements, experiments, demonstrations, conjectures , tests, theories, publications, applications, etc. The philosophy of science should only deal with scientific knowledge, and not even its elaboration, dissemination and learning, but only its formulation. It was a positivist philosophy of science in the strong sense of the word, because it only interested the results, not the processes that led to those results and rejected others.

These philosophical assumptions are inadequate for technoscience. The techno-scientific revolution is characterized by a change in the structure of scientific activity. It also transforms knowledge, but these modifications are not as significant as the transformations of scientific practice. As we have been checking throughout this work, the technosciences incorporate new agents and new actions. Returning to Latour’s question, who does science ?, we will say that technoscience is not only made by scientists and engineers, but also by governments, companies, experts in science policy and in science and technology management, the military, the jurists who define the legal frameworks for the techno-scientific activity, the ecologists who answer some actions and results of the technoscience, the financiers and patrons who support the investigations, etc. The techno-scientific enterprise is an activity that covers a spectrum of professions much wider than that of the scientific-technological communities of modern science. Even citizens and users, although they do not do science directly, can influence techno-scientific activity. Some countries systematically measure the opinion and attitudes of citizens with respect to technoscience. The rejection or doubts of society regarding the experts in science and technology, previously unquestioned, is one of the most important problems of technoscience. It tends to transform societies, as we have stressed time and again, but societies have ceased to be passive and are not easily transformed, let alone dominated by technoscience. The social power of technoscientific devices, for example the military, is enormous, but it raises more and more criticisms and dissents.

Philosophically speaking, it is necessary to affirm the plurality of techno-scientific agents, or in more classical terms, the plurality of the subject of technoscience. However, not all of these agents are equally relevant. Therefore, we distinguish between agents integrated in the core of technoscience and peripheral or orbital agents. In the case of military macro-science, the core includes at least five types of agents: military, political, scientific, engineering and industrial. The civil macrociencia dispenses with the first, but includes managers and even experts in law. In the case of techno-scientific companies, financiers, entrepreneurs, managers, lawyers, scientists and engineers are part of the core of technoscience, although political and institutional support should also be available, if necessary, and a good social reception. The latter can manifest itself in the market (consumers), but also as public opinion. Hence the enormous importance of the social perception of technoscience. On the periphery of technoscience are the environmental groups, the media, foundations and intermediation companies. In specific disciplines we must also count on cultural, moral and religious factors, since they have a great impact on public opinion, and may even have it in the market. The internal equilibrium of the plural agent of technoscience is difficult to achieve, as shown by the existence of continuous conflicts, both in the nucleus that directs techno-scientific actions and in the periphery. What must be ruled out is the existence of a subject of technoscience that is autonomous and coherent, in the manner of the Cartesian or Kantian subject. The structural complexity of the techno-scientific activity is immediately reflected as the complexity of the techno-scientific agent. Hence the importance of equipment (research, management, financial support, etc.). When Bush told Roosevelt that scientists had to team up with other social agents, he foreshadowed one of the main structural features of technoscience.

IV.7: Techno-scientific actions.

A philosophy of technoscientific activity can advance very little if it does not have a theory of action, and also uses it. In section I.7 we discuss the definition of technology proposed by Quintanilla and add some improvements. It is now a matter of applying those ideas to techno-scientific actions, previously specifying the notion of action, which in this definition was not analyzed.

In this section we characterize technology as a system of regulated, industrial actions linked to science, carried out by agents, with the help of instruments, and intentionally oriented towards the transformation of other systems in order to achieve valuable results avoiding consequences and unfavorable risks. That definition is still valid for technoscience, but it must be completed with the various distinctive features that we have established in sections II.1 and II.2. Therefore, the term “industrial” has to be eliminated, because we saw that technoscience is linked more to the informational society than to industrial society, unlike macro-science. This does not mean that it does not have industrial components, but that informational ones predominate. Therefore, we will replace “industrial” with “informational”.

Secondly, technoscience is not only linked to science, but also to engineering, politics, business and, where appropriate, military organizations. This implies a new modification in definition 3, which should be left open, without closing the number of agents involved in the core of the techno-scientific activity, because we see that this nucleus can include more than five basic agents, depending on the type of techno-scientific company that we are studying.

Third, we are interested not only in technical or technological achievements or applications, but also in more complex entities, the science and technology systems (SCyT). According to the theory of systems, the SCyTs integrate a great diversity of subsystems, for example the diverse agents that we have distinguished in the inner section. A government agency, an R & D company, a university, a laboratory, a particle accelerator, a computer equipment, an advisory or evaluation board, etc., are subsystems of the SCyT system. Each of the components of the SCyT system is in turn a system, which can be political, business, military, scientific, technological, etc. On the other hand, also objects investigated by technoscience are systems, be they mathematical, cosmological, physical, chemical, medical, biological, geological, economic, social, technological or otherwise. Our basic ontology is systemic, since we accept that the framework in which techno-scientific activities are developed, the SCyT system, affects the other subsystems that are part of it, giving meaning to concrete techno-scientific actions. Therefore, we are interested not only in technological achievements or applications, but also in technological systems, whether small or large. We will replace the term to be defined by the notion “technological system”, meaning the SCyT system and all its subsystems, which are many and very diverse.

The rest of definition 3 is still valid, so we can propose as a provisional characterization of technoscience the following:

Def. 4: “A techno-scientific system is a system of regulated, informational actions linked to science, engineering, politics, business, armies, etc. These actions are carried out by agents, with the help of instruments and are intentionally oriented to the transformation of other systems in order to achieve valuable results avoiding unfavorable consequences and risks “.

We emphasize again that it is not a definition in the logical sense of the term, but simply an initial characterization, which allows us to clarify minimally the concept of “technoscience”, as opposed to “technology” and “technique”. Regarding the differences between science and technoscience, sections II.1 and II.2 were sufficiently explicit.

Successful or not, definition 4 is an analytical instrument that can be useful to develop a philosophy of technoscience, as was our initial purpose. We insist from the beginning that this philosophy is oriented to scientific activity, rather than to knowledge. Therefore, we have to clarify minimally the concept of action that we use, always from a philosophical perspective.

In this regard, in a previous book we have proposed some rudiments of action theory 201, which, with very few modifications, we will continue to assume and use when talking about techno-scientific actions. With this, both notions are clear, that of “action” and that of “technoscience”. The point is now to show that this conception of techno-scientific actions is broad enough to reflect the great diversity of aspects of techno-scientific practice.

That theory of action distinguishes several components, one of which is the results of the actions, but not the only one, and sometimes not the most important one. There are at least twelve components of techno-scientific actions: the agents, the actions, what is done, the entities that are acted on, the instruments, the context or situation, the initial and contour conditions, the intentions, the objectives, the results, the consequences of the action and the risks that could arise from it. Therefore, the actions are represented by n-uplas of twelve or more components, A = Ai, some of which will be more relevant than others when analyzing a techno-scientific action A. The actions take place along the time, A (t) = Ai (t) , which does not imply that we conceive them as linear processes or sequences of events. The components can change and feed each other. That is why we speak of systems of actions, not isolated actions. For example: the initial results of an investigation may require the incorporation of new agents (as in the Manhattan project), of instruments (as in the ENIAC project and the Genome project), of different initial conditions (a new legislation for patents, the reduction of R & D activities, new financing …) and even objectives (the space telescope became an instrument to observe the planets, not only the galaxies). Techno-scientific actions are developed over time and its components are changing in that direction: a certain result, for example the discovery of the spontaneous fission of plutonium in the Manhattan project, can radically modify the direction of research. The project remains the same, but there is a change in the agents, the instruments, the initial and contour conditions, the objectives, etc.

On the other hand, we must not only deal with classical scientific actions (observe, measure, experiment, publish, present a project, publish, patent, etc.), but also pre-actions, that is, the design of experiments, the presentation of projects, their realization, their results, etc. We will not enter into these questions here, because they have been widely exposed in the book Science and Values. In conjunction with definition 4, we will use that theory as an instrument for our analyzes of technoscience. Being very general, it can be applied to experimental actions in laboratories, to communicative actions in scientific communities (congresses, magazines, telematic networks), to scientific-technological policy actions, to the industrial implementation of techno-scientific innovations, to the dissemination of knowledge in society, etc. The usefulness of these two conceptual instruments with which we have endowed is worthy of consideration: given a large techno-scientific system or action, for example a scientific macroproject, we can analyze one by one the different types of actions necessary for its development, as well as the components of their actions.

Instead of only dealing with what is done in laboratories or the knowledge that emerges from them (facts, measurements, experiments, hypotheses, theories), we will also have to study what happens in other technoscience scenarios: scientific policy offices , committees of the Congress, committees of evaluation of the pre-projects, companies interested in its development, etc. Contrary to what is usually thought, these new scenarios are part of the interior of technoscience and it is necessary to study them with philosophical, historical, sociological, economic tools, etc. Technoscience is a much broader and more complex system than modern science. Science and technology studies must be able to analyze it in all its scope and complexity. We think that the two conceptual instruments that we have proposed are valid for this.

There is a key aspect in the theory of action that we use, namely: all its components are evaluated again and again, according to systems of values differentiated according to the components. The enormous complexity of the notion of “techno-scientific action” does not prevent the existence of a path of analysis common to all the components: axiology. Although the concept of technoscientific action may seem intractable due to the great diversity of notes and distinctive features of technoscience and action, in the aforementioned work we introduced two instruments of axiological analysis, matrices and evaluation dimensions, both strictly formal. The agents, the actions, the instruments, the situations, the objectives, etc., are very different according to the techno-scientific actions, but all of them can be analyzed through the formal representation A (t) = Ai (t)  and subsequently evaluated by the expression cijk (t)  vijk (Ai (t))  Cijk (t). In chapter 5 we will explain in more detail the usefulness of matrices and levels of evaluation for the philosophy of technoscience. For the moment we limit ourselves to pointing out that, given two techno-scientific actions A and B, for example two research projects, as well as their respective Ai and Bi components, the evaluation matrices allow formalizing the selection processes of one or the other. To do this, the proposing agents (knowledge, curricula, technical capacities), the actions to be carried out (work plan, strategy, phases), the required instruments (financing, equipment, additional human resources), the initial conditions (previous achievements) are valued of said team or company, state of affairs), the boundary conditions (collaborating institutions, co-financing), the methodology to be followed, the objectives, the expected results and, where appropriate, the risks that may arise from the investigation. Projects A and B are compared component by component, scoring in each case the valuation assigned to each component. If the nuclear values are not satisfied above their minimum level (or the disvalores below the maximum level), the project is rejected. By successive iterations, and resorting to various value systems, the evaluation process culminates and can be adequately represented through a succession of matrices and levels of evaluation. Therefore, the changes that can be made during a selection process or in the decision making in favor of a macro project in relation to an alternative one can be formally represented. This is true in principle for any type of technoscientific actions or proposals, so that axiology provides an instrument of analysis of great interest. If, instead of having to select between two or more research projects, it is about naming a person to direct a macro project, or to chair a commission, or to manage a techno-scientific company, the evaluation process is very similar to the one before described, although the evaluation criteria and the objects assessed are heterogeneous. The great advantage of distinguishing formal components in a notion, be it “action” or “technoscience”, consists in the fact that we can then compare heterogeneous entities with each other, as the various evaluation processes that occur in the activity techno-scientific In chapter 5 we will return to these questions.

To finish this section, we will return to some of the considerations made in the previous chapter. We saw that scientific revolutions and techno-scientific revolutions are differentiated by the agents that carry them out. Sociologically speaking, Kuhn identified the paradigms with the scientific communities that advocate, develop and institutionalize them. The scientific community also participates in the techno-scientific activity, but not only it, as we saw in Chapter 2. Some techno-scientific revolutions can be promoted by companies, others by military agencies or by environmental groups, others by politicians … Neither scientists nor Engineers have a monopoly to promote techno-scientific changes, even if they are necessary to carry them out. Well understood that this plurality of techno-scientific communities is made up of individuals, who are the ones who ultimately perform techno-scientific actions, usually in groups. Unlike the groups of scientists Kuhn talked about, techno-scientific companies are always transdisciplinary, so they have to be able to integrate and harmonize, even partially. In general, the subject of technoscience is a plural agent, formed by representatives of the diverse communities that participate actively in the development of the techno-scientific action A = Ai. Note that these agents can be relieved, that is, they can be replaced by others over time. The first component of techno-scientific actions, therefore, is variable over time, as will others. There is no timeless subject of technoscience, nor of science, on the other hand. Of course, pace Popper, there is no technoscience without a subject, because of the eminently historical character of it. The difference is that the subject of technoscience is structurally plural. There is no Newton or Mendel in the case of technoscience.

Having a plural subject can not be inferred that technoscience is a subjective issue. Throughout the techno-scientific activity we must distinguish between moments of subjectivity, which also exist, moments of intersubjectivity and what we might call moments of objectivity: when an artifact works or not, when an atomic bomb explodes or breaks down nuclear reactor, when a satellite arrives or not at the intended target, etc. The effects of the atomic bombs of Hiroshima and Nagasaki, for example, were objective, regardless of whether they were also intersubjective and subjective. Note that objectivity is predicated in the first place on the actions (whether they were carried out or not) and only in the second place of their results, among which are the facts. In a philosophy of scientific practice the problem of the objectivity of technoscience shifts from facts to actions.

IV.8: Technoscience and cultures.

Since Snow spoke of the two cultures (1962), humanistic and scientific, science has changed a lot. One of the most important issues to face is the relationships between technoscience, society and culture. We do not intend to address it here, but it is appropriate to make a few considerations, in order to highlight some of the major changes that have occurred in this regard at the end of the 20th century.

First, technoscience affects several societies, not just one. When sociologists subsume science in society they forget this problem, which is not trivial, far from it. Today’s technoscience is expanding throughout the planet, due to the fact that the application context of science and technology has surpassed the national borders. Techno-scientific companies are organized as network companies and develop their strategies in several countries. Such is the case of pharmaceutical and biotechnology companies, as well as information and communication technology companies. The same applies to the classic industries (construction, metal, transport …), which operate in an increasingly wider market. The emergence of technoscience coincides over time with the expansion of the market, which was one of the structural components of SCyT systems. Therefore, there is no subsumption of technoscience in a society, not even in the United States, but impacts of technoscience on several societies, which must be analyzed separately. On the other hand, the technoscience itself shows different characteristics depending on its places of origin, although it must be redesigned for each specific market. The new techno-scientific culture is international in its structure (networked techno-scientific enterprises) and not only clashes with traditional scientific and humanistic cultures, but also transforms local cultures, with consequent conflicts. 

The relationships between technosciences and cultures have to be analyzed contextually, case by case, which will not be easy to do. To reduce the problem to the debate between the two cultures, the humanistic and the scientific-engineering, and to try to solve it with a third culture that synthesizes the other two, supposes an enormous simplification, in which the existence of a plurality of technosciences and cultures is forgotten.

When we say these things, we are not thinking only of multiculturalism, understood as a function of the countries and regions of the planet, but of the radical differences that exist between the military, business, legal, scientific or technological cultures. All these social sectors are embedded in the core of technoscience and provide very different cultural traditions. The clash between cultures occurs within the bosom of technoscience, not only when it transforms societies. This is why we are primarily interested in the internal conflicts in techno-scientific companies, as well as the disputes between competing companies, insofar as they embody different cultural and organizational models. Technoscience is not only the work of scientists and engineers, but also of many other agents who act according to very different cultures and values. The social component of technoscience is undoubted, but this is very little to say. The important thing is to specify the different social agents relevant to the techno-scientific activity and analyze the problems that this multiple (or plural) agent has when developing its activity. Who subsumes the science in society is like who subsumes the multinational companies in societies. Just as macro-science emerged in a strictly national sphere, techno-scientific companies design their strategies thinking in global markets. The important thing is to analyze their respective practices, as well as the confluence of these practices in various scenarios, some of which are traditional (laboratories, publications, scientific-technological institutions, patent registrations, etc.), others new. As we have pointed out above, one of those new scenarios of technoscience are the scientific-technological policy cabinets, whether governmental or business. Another is the market, which tends to be global, especially in the case of techno-scientific innovations. The practices, the conflicts, the arguments and, where appropriate, the consensuses, are very different in each and other scenarios.

Thus raised the problem, opens a wide field of research. For our part, we will only deal with conflicts of values, understanding that values are an essential component of cultures. In particular, we will be interested in those conflicts of values that show a greater universality, because they are internal conflicts to the technoscience itself. For example, the distinction between public and private technoscience is a structural difference, which makes technoscientific activity very different. The agents, the organization of the actions, the underlying interests, the objectives, the evaluation criteria and a good part of the practices differ considerably in one case or another. It is of little use that, from the point of view of the results of the research or innovative activity, the results coincide, or are comparable to each other. The race between a public and private team to establish the map of the human genome is a good example in this regard. The practices are different, and above all, the values that guide these practices are different. Bearing in mind that the dominant techno-scientific paradigm gives private companies a large part of the chain links mentioned in the previous section (technological development, innovation, production, marketing, etc.), private agencies (companies, consultants, etc.) predominate to a great extent over public ones in technoscience, despite the fact that the latter assume the strategic direction and a good part of the financing. The business culture has an increasing weight in technoscience.

In order to thoroughly analyze the relationships between technosciences and cultures, much more detailed research would be required. The suggestions we have outlined here are only a first sketch of that study. The comparison between the policies of specific techno-scientific companies, some public and others private, would be of great interest for the studies of technoscience. We leave this investigation open, after having sketched some of its main lines.

Chapter V Axiology of technoscience

V.1: Technoscience and values.

The techno-scientific practice can be studied from many perspectives: one of them is the axiological one. The evaluations of the scientific-technological actions are produced continuously, including those of their results. If we maintain the distinction of four contexts in the scientific-technological activity, the one of education and diffusion, the one of investigation and innovation, the one of application and the one of evaluation, the axiology is nuclear in this last context. In this chapter, we will focus on the context of evaluation of technoscience and its relationships with the contexts of research and application, given that in other publications we have already dealt with values in the context of education 202.

We do not intend to value technoscience as a whole. As León Olivé says, “it is not possible to morally evaluate science and technology in general or in the abstract” 203. However, “concrete technical systems are subject to moral evaluations and are not ethically neutral” 204. It is important to take into account account this when talking about the axiology of technoscience. It makes no sense to ask, except on a subjective basis, whether technoscience in general is good or bad, dignified or unworthy, just or unfair, solidary or unsupportive. On the other hand, we can assess specific techno-scientific systems, understood as systems of human actions and not as sets of artifacts, as we saw in section I.7. We will focus on the assessment of techno-scientific actions, including their results, their consequences and their risks, following the line opened in the book Science and Values, whose basic hypotheses continue to be developed in this work 205. In some cases, such evaluations can be made from an ethical perspective. Some techno-scientific actions raise important moral problems, both in the scientific-technological communities and in society in general. But not all. The axiology is broader than the moral. Apart from ethical assessments, techno-scientific activity can be judged from many other points of view. The epistemic, technical, economic, political, legal, ecological, social values, etc., are also relevant to the axiology of technoscience. Therefore we will devote section V.2 to distinguish the different types of values relevant to technoscience.

On the other hand, the axiological actions are very different according to the different contexts of the techno-scientific activity, as well as according to the agents, the evaluated, etc. Let’s see it briefly, applying to the act of evaluating the theory of action that we have proposed previously.

In the context of education and dissemination there are different evaluating agents. On the one hand the scientific-technological community, represented by the professors of the different educational levels and the directors of centers. A teacher not only teaches, he also evaluates. They are two very different actions. At the same time, the teaching activity is evaluated, as well as its final and intermediate results. In addition, textbooks and teaching instruments are evaluated, as well as schools, universities or the education system as a whole. As we consider more axiological actions in the context of education, we find that scientists and engineers are not the only ones who carry out evaluations. Although it is based on more subjective criteria and through non-standardized procedures, parents also evaluate, as well as the students themselves. The society in general, and more specifically the States, usually institute their own evaluation systems: revalidations, tests of selectivity and access to universities, quality agencies, cost analysis, etc. The evaluation context interacts everywhere with the educational context through very different agents, processes and evaluation criteria. The good / bad dichotomy is only one of the criteria to be taken into account. You can also evaluate the competence, efficiency, cost, utility, social integration through education, advances in the level of literacy of a society, etc. Regarding the diffusion of science and technology, the main actions are carried out by other agents and with other media: scientific dissemination magazines, radio and television programs on science and technology, books, web pages on the Internet, museums of science and technology, etc. When a visitor to a science and technology museum fills out a survey questioning his impressions after the visit, he is doing a user evaluation. The experts in electronic documentation have developed very sophisticated systems to assess the quality of Web pages. In general, the various actions of techno-scientific dissemination are always valued, and not only in the market, depending on the audiences or sales indexes, but also through other instruments: surveys on the perception and attitudes of society to science and technology, impact and influence indexes, quality indicators, economic cost / benefit analysis, etc. In the context of education and dissemination there are many evaluations. All of them have axiological interest and, of course, not all are of a moral nature, much less. There are subjective evaluations (for example those of a student, those of a parent or those of a teacher), intersubjective (average grade in a course, academic record, …) and objective, meaning the latter those that are carried out through standardized evaluation protocols, so that the results do not depend on the evaluating agent, at least in principle. Some of the results of the evaluations are made public, others remain in private, or even intimate. In summary, given the great complexity and variety of axiological actions in the context of dissemination, it is essential to analyze and distinguish the types of axiological actions, as well as the kinds of values, agents, situations, results, teaching tools or informative, etc. This is how the theory of action exposed in the previous chapter is applied to the context of education and dissemination. Our axiology of technoscience will be analytical and empirical, as we have already advocated in the book Science and Values.

In the research context something similar happens, but corrected and increased. Modern science has created a specific system of evaluation of scientific publications, the peer system review system, which is one of the most unique characteristics of science from the point of view of evaluation. This system has been expanded to various disciplines and different countries, which is not to say that it prevails everywhere. In fact, one of the quality indexes of a scientific publication depends on the existence of an anonymous and peer evaluation system. Subsequently, this evaluation model was implemented in other areas of the research and innovation context. One of the distinctive features of public technoscience consists in the comparative evaluation of research projects, requests for infrastructure, organization of congresses, appointments, allocation of jobs, technological innovations, etc. To this end, various Science and Technology Evaluation Agencies and Committees were created. The context of evaluation of science has its own institutions (doctoral thesis tribunals, commissions for competitions and university competitions, commissions for allocation of public funds, hiring commissions, etc.), which make decisions on the excellence of researchers, the suitability and reliability of the equipment, the quality and prestige of the universities and the research centers, etc. In some cases ethical problems arise (falsification of data, plagiarism, dishonesty), which are usually solved by scientific communities based on deontological rules that the communities themselves establish 206. However, apart from ethical problems, in scientific research There are many other value conflicts. Not only epistemic conflicts occur, such as the incommensurability between rival paradigms, or the contradiction between hypotheses, theories and predictions, or the imprecision of observational data, measurements or experiments, or the lack of rigor of some proposals, nor not only conflicts between technical values, such as utility, efficiency, applicability, robustness or good or bad performance of the devices, but also conflicts that depend on economic, social, political, legal, ecological or military values. Therefore, in the research context there are many other evaluation processes, apart from the anonymous peer system. Governments have their own political-economic criteria, and in their strategic-military case, to evaluate the techno-scientific programs and the institutions dedicated to research. The same applies to large companies and their R & D Departments. Since innovations compete with each other in the market, this can be considered as an important valuation agent: it is the one that assigns value to said innovations, in the economic sense of the term “value”. Other social groups also make their own estimates, showing greater or lesser confidence in scientific research and in the judgment of experts. Although the system of evaluation by pairs is very important and has become generalized, it is not the only system to be taken into account. From an axiological perspective, technoscience is distinguished from science and technology by the greater plurality of value systems involved in evaluation processes. Instead of asking the vague question of whether technoscience is good or bad, we must analyze it case by case, based on empirical data and using previously designed and standardized evaluation criteria. All this as far as possible, of course. In the context of research and innovation we can also distinguish between purely subjective evaluations, which exist, and are very frequent, although little attention is paid to them, intersubjective evaluations (which imply consensus processes between different evaluating agents) and objective evaluations. In the objective evaluations, standardized evaluation protocols are used: at least in principle, they offer similar results regardless of who the evaluating agent is. The objectivity of some evaluation processes does not imply axiological neutrality. The myth of neutrality and value-free science must be eliminated from the reflection on technoscience. The instruments used by scientists and engineers to evaluate their own research instruments, the reliability of the results, the impact of the results, etc., are loaded with values, at least of epistemic and technical values. In the case of technoscience, they are also usually loaded with economic, business, military, political and legal values, as we saw in the second chapter.

Objectivity is a value, a core value of technoscience, which is part of a value system and only acquires meaning in that systemic framework. On the other hand, in the context of research and innovation there are public evaluations, but not all of them are. Many of them are produced in private areas, including the private forum of the various techno-scientific agents: scientists, engineers, technicians, businessmen, politicians, etc. This plurality of value systems and evaluating agents is much broader and more complex in the case of technoscience than in that of science and technology. Therefore, we affirm that value conflicts are an integral part of techno-scientific activity, because they derive from the axiological structure of scientific-technological practice. In the science and technology of the industrial age they also existed, but in many cases they could be solved within the scientific-technological communities. In the case of technoscience, this is no longer possible, as we saw in section III.6, when referring to techno-scientific contests. The subject of technoscience is structurally plural and therefore is in conflict with itself. The scientific and technological communities have an important role in the conflicts of technoscience, but not only them. Both during development and in the eventual resolution of conflicts, many other agents intervene, whose value systems are neither epistemic nor technical. Therefore, it is essential to analyze the different kinds of values relevant to technoscience. As we said in the previous chapter, the values characterize the various subcultures that are integrated into the techno-scientific culture.

What we have just said about the research context is even more valid in the context of application. Techno-scientific discoveries and innovations not only apply to nature, but above all to the transformation of societies and the lives of people. Wars based on technoscience are the clearest example, but there are many others: genetic engineering, pharmacology, technomedicine, information and communication technologies, advertising, behavior modification techniques, surveys on voting trends, macroeconomic models, etc. When societies and human beings become the object of techno-scientific actions, then necessarily reactions arise, or if you want critical responses, acceptances, oppositions, etc. The context of application of technoscience is, above all, society, so there is no point in trying to separate the techno-scientific activity from social life. The plurality of values and evaluating agents increases exponentially in the context of application, and with it acceptances and conflicts. It is literally impossible to elucidate whether technoscience is good or bad for society, in the first place because there are many societies and many technosciences, but first of all because the diversity of value systems is much greater in the context of social application of technoscience. Some technoscience, such as an intelligent missile, or a synthetic drug, will do very well. To others very badly. Most of the assessments in the context of application are subjective and intersubjective (for example cultural), few can be classified as objective. One of them is the voting system following the rule of the majority, which is applied again and again in the techno-scientific activity for the resolution of conflicts: for example in courts, in the commissions that assign projects, or in the parliaments that approve laws and science and technology plans. Another is the evaluation by experts, according to a previously established procedural rationale. The main problem is to establish protocols and standardized and public evaluation procedures, which must be done before starting the evaluation processes. To achieve this, it is necessary to reflect on the action of evaluation and on the instruments that facilitate it. A parliamentarian who works in a science and technology commission, like any other commissioner, must have procedural rules and instruments to carry out his task, apart from his own criteria as an evaluating agent. We can conclude, therefore, that the definition of technoscientific action that we proposed in section IV.7 also applies to evaluation actions. Evaluating technoscience is (must be) a techno-scientific action. Hence the importance that we attribute to evaluation instruments, which are not reduced to the good or bad judgment of the evaluating agents.

It should not be forgotten that, since the origin of technoscience, many “controversies” between rival programs were solved by way of military contention. The main purpose of this book is to propose civil methodologies for the resolution of value conflicts in the context of the application of technoscience. These civil methodologies are not based on the theory of rational decision or instrumental rationality, which are the two forms of rationality that prevailed in the industrial era. This purpose is difficult to achieve, since it is not enough to find a possible social methodology for the resolution of these axiological conflicts. A trans-social methodology is required, since we have already stressed that technoscience affects several societies at the same time, not one. We will return later on these problems, which are very arduous, but we can anticipate that in the context of the application of technoscience the existence of very diverse cultural and social values can not be rejected. It is about configuring a minimum system of shared values to civilly solve the various conflicts generated by technosciences. Some will think that it is an impossible task. But there are precedents of similar axiological actions, such as the Declaration of Human Rights of 1948, which instituted a system of basic values to guide political-social life. Given the growing importance of technoscience in contemporary societies, it is about establishing a social contract for technoscience based on axiological pluralism, and not on the predominance of certain business and political values that allowed to reformulate the report of Vannevar Bush after its crisis In the 70s.

The preceding paragraphs show the scope of the challenge. We insist that the axiological perspective in which we situate ourselves is not the only possible one: the praxiology of technoscience is not reduced to the question of values, and we must not forget that epistemology, history, sociology and economics of technoscience continue to have great importance in science and technology studies. However, we consider that it is one of the lines of philosophical research that can contribute most today to the studies of science, technology and society (CTS), which are the framework in which this book is located. Briefly recalling the emergence of the philosophy of science at the beginning of the 20th century, it can be affirmed that the appearance of CTS studies is a consequence of the very emergence of technoscience after the crisis of macroscience in the decade 1965-1975. The Philosophy of Science and the History of Science were constituted as academic disciplines in the first decades of the 20th century, to our understanding as a consequence of the great changes and revolutions that had taken place at the end of the 19th century and the beginning of the 20th century in the field of Biology (Darwin, Mendel), Mathematics (non-Euclidean geometries, set theory), Physics (theory of relativity, quantum mechanics) and social sciences (Experimental Psychology, Mathematical Economics, Empirical Sociology, etc.). The Naturphilosohie of the German Universities proved insufficient to think those great scientific changes and for that reason a Philosophy of Science of logicalist, empiricist and positivist orientation arose. Well, at the end of the twentieth century there was a change no less important in scientific activity: what we have called the techno-scientific revolution. As a result, in the 70s emerged the two main lines of what are now called CTS Studies: the North American school (Mitcham, Durbin, etc.) and European (Strong Program, ethnomethodology, etc.). The analytical philosophy of science and technology was unable to assume that science itself had changed and continued to maintain its basic program, focused on the analysis and reconstruction of theories and scientific knowledge, without any attention to practice. The Praxiology of science and technology still does not exist as a discipline, nor does Axiology, although in this there have been important advances in recent years (Laudan, Rescher, Longino, etc.). Well, CTS studies are children of technoscience and come to fill the gap left by the philosophy of science, which, except for honorable exceptions, remains focused on modern science, without even accepting the emergence of technoscience. The axiology that we advocate is a philosophical contribution to the interdisciplinary studies of science, technology and society, rather than to the philosophy of science in the strict sense of the word. Let’s see what are the bases on which it sits.

V.2: Types of values.

In this section we will analyze the different value systems that affect the techno-scientific activity. For this we have to face two delicate problems: what are the values and what kind of values are there? With regard to the first question, we have already expressed our position 207 widely: we do not consider values as essences or entities, much less as timeless, but as functions (in Frege’s sense) applied by evaluating agents to systems of scientific actions , technological or techno-scientific. With respect to the second, different criteria can be introduced to classify the different types of values. On our part, we follow an empirical criterion, based on the observation of the techno-scientific practice, as it has been described in the previous chapters. Other authors propose more systematic classifications, some of them very interesting, such as the one recently presented by Juan Ramón Alvarez Bautista 208. However, in this work we will continue to focus on the distinction of twelve relevant subsystems of values for the axiological analysis of techno-scientific practice , as indicated in the book Science and Values:

1.- Basics

2.- Epistemic

3.- Technological

4.- Economic

5.- Military

6.- Politicians

7.- Legal

8.- Social

9.- Ecological

10.- Religious

11.- Aesthetics

12.- Morales

Each of these subsystems groups different values. Not all of them affect the different disciplines, neither in each historical moment, nor in each specific techno-scientific action. However, all these types of values can be significant when jointly evaluating techno-scientific actions and their results. The evaluation processes are usually iterated, and even recursive. The linear model of Bush presupposes that scientific discoveries are valued first, based on exclusively epistemic criteria. Next, their applications and technological implementations are evaluated, based on technical values. Once these criteria have been met, the product design phase is passed, in which other types of estimates are already taken into account, as well as in the subsequent stages of the production, marketing and use of the devices. Finally, the market makes its own valuations, as does society. In the sixth field of SCyT systems, military organizations also have their own criteria for evaluating techno-scientific innovations. At the periphery of the system, other value systems (ecological, moral, aesthetic, religious) can be distinguished, some of which may be very relevant in specific circumstances and areas, for example in a fundamentalist state that seeks to promote technoscience. The same is true of users, who can make their decisions based on aesthetic criteria or subjective reasons, assuming that the products they have to choose from have exceeded the minimum thresholds for nuclear values, and therefore have been disseminated in the market.

From the axiological perspective, technoscience is characterized by a mixture of heterogeneous values, since it arises from a stable alliance between diverse social agents, whose actions are guided by different value systems. Many investigations are promoted because of their possible military, economic or political interest: epistemic and technical evaluations are secondary in this case, although they also exist, but not as an objective, but as a necessary requirement. The Manhatan project, for example, was not designed and driven for epistemic or technical reasons, but primarily for political-military needs. The undoubted scientific and technological advances that it generated were subordinated to the objectives of this project, as we saw in section II.3. The same is true of the ENIAC Project, the exploration of space or the Genome project. For their promoters and financiers, the epistemic advances that they provoked were instrumental. In general terms, and contrary to what Bush affirmed: if techno-scientific companies finance basic research, it is not to advance the frontier of knowledge, but to try to achieve its ends, which tend to be much more prosaic than the search for truth. Scientific knowledge is an instrument for techno-scientific companies. Investors do not invest in R & D for scientists to propose new theories. These advances are welcome, but only because they suppose prestige for the corresponding corporation or institution, which can contribute to alleviate public distrust, to gain the confidence of private investors or to guarantee public financing. The example of the TIGR Institute, created by Rosenberg under the sponsorship of a nonprofit Foundation, but with a company created to commercially profit from the gene sequencing of Craig Venter and his team, illustrates the axiological plurality of the techno-scientific practice and the subordination of epistemic values to business values. In other cases, the subordination of advances in knowledge occurs in relation to the military or political objectives that underlie most techno-scientific actions, especially if they are of great importance.

If we want to have a general theoretical framework for the axiology of technoscience, it is necessary to consider at least those twelve subsystems, since they all play a role in the design and evaluation of techno-scientific proposals. Next, it is necessary to empirically explain in each case what is the order of effective application and the relative relevance of one or other subsystems. All this without prejudice to the fact that some other subsystem could be added, for example by breaking down the subsystems of epistemic, political, moral values, etc. In general, when we study specific cases of technoscience we will not have to consider the twelve subsystems, but a few. The techno-scientific activity almost always involves epistemic, technological, economic, political and military values. In some cases, ecological values are added, in other legal, social, moral or religious values. There are occasions in which aesthetic values are very important, inclining the decision in favor of one proposal or another according to their aesthetics. The same can be said of legal values, or of ecological values. In summary, of these twelve subsystems we will have to select a few to carry out the case-by-case study of technoscience from an axiological perspective. The axiology of the technoscience that we advocate is analytical and empirical. The first thing that must be specified is the order of the evaluations and the specific weight of each subsystem or value, instead of presupposing a stable hierarchy in the value system that guides the techno-scientific actions. In some cases the utility will prevail, in others the precision or the expected economic benefits. The axiological functions are applied by the different evaluating agents according to different weights, which have to be determined empirically in each case. This does not prevent, of course, that the empirical analysis show the absence of certain values, or their relative relative weight when approving or rejecting certain actions. Faced with an abstract critique of technoscience, typical of lazy rationality, the axiologists of technoscience must take the trouble to analyze the values at stake beforehand, in order to intervene in the debate introducing new evaluation criteria or modifications in the relative weights of the values actually intervening. The moral condemnation of technoscience is very satisfactory from the point of view of good individual conscience, but completely imprecise and ineffective when trying to modify techno-scientific practice.

By distinguishing these twelve subsystems we are proposing a classification of the values of technoscience. This classification is provisional and improvable. Other classifications are much more systematic, such as the one proposed by Alvarez Bautista. This author distinguishes between communicative, economic and social values, on the one hand, and, depending on a second criterion, between liberating (desiderata), eliminatory (demands or duties) and nuclear values. His proposal is of great interest, but commenting on it thoroughly would take us a long way, so we will keep our own classification for now, which has to be understood as an open table with internal feedback. There are values, such as freedom, that can be understood from very different meanings: as a basic, epistemic value (freedom of investigation, freedom of education), political, legal, business, social, etc. Therefore, the twelve subsystems are not authentic classes of equivalences, but subsystems that interact with each other in concrete situations. Hence the importance of the initial and contour conditions when carrying out evaluations. The information available, for example, is decisive for the results of the evaluations to be one or the other.

The various classifications of values presuppose philosophical conceptions and ours is not an exception, although in pureness it is not a classification, as we have just pointed out. Before proceeding, it is convenient to make explicit two of its fundamental assumptions.

In the first place, we chose a systemic perspective when studying the values of technoscience. Instead of considering each value separately (axiological atomism) and accepting that it has a meaning per se, we start from the hypothesis that the values are applied together, so that when evaluating an aspect we also put other values into play. This systemic character, which we have already referred to elsewhere 209, implies affirming the existence of various subsystems of values Vj in technoscience, varying the subscript j from 1 to 12 (or more), since we have distinguished twelve subsystems of values . Each subsystem Vj in turn includes a plurality of interconnected values Vjk. For example, in order to calibrate the likelihood of a hypothesis, it is necessary to assess its internal and external coherence (that is, also in relation to other credible hypotheses in said scientific discipline), the precision of the observations and measurements that allow corroborating or refuting it, the realizability of the experiments that could confirm or refute it, etc. A certain epistemic value is co-implicated with other epistemic values, as well as with other non-epistemic ones. Therefore we speak of systems and subsystems of values, rather than elementary or atomic values that could be grouped into twelve or more equivalence classes. The same value can be included in several subsystems, although, if this happens, it will not be applied in the same way in either case. In other words: this value does not have the same meaning as it is integrated into one or another subsystem. 

This does not suppose any “paradox of the meaning”, as the philosophers of the science of the inherited conception used to say (received view), since the values, depending on axiological functions, only acquire meaning when said functions are applied to evaluate an action or a specific component. The existence of a plurality of subsystems generates an internal tension to the value system of technoscience, which manifests itself in the form of conflicts of values, as we have emphasized more than once. Although our axiology is analytical, it aims to analyze the “dialectic” internal to the value systems of technoscience. It is one of the main peculiarities of our approach. In other words: the axiology of technoscience is dynamic, not static. The important thing is to elucidate the systems of shared values at a given moment, independently of the fact that in such systems there are conflicting values among themselves.

Secondly, concrete values are emerging, that is, they arise over time and from the evaluation processes, starting from initial values. One of the most notable characteristics of twentieth century technoscience was the progressive emergence of a new subsystem of values, ecological values, which had barely been taken into account in modern science, but which in the second half of the century have been acquiring a relative weight of certain significance in scientific and technological activity. Nowadays, a scientific laboratory worries about the problem of the elimination of the residues of its experiments, which was not usual at the beginning of the XX century, much less before. Although ecological values are not the most relevant in the research context (something more in the application), they have a certain role when it comes to assessing techno-scientific research. Therefore, they must be considered as a specific subsystem, whose relative weight grows gradually. The same could be said of business or legal values, which have been gaining increasing weight in technoscience throughout the 20th century. The values of technoscience are not consubstantial to it, although there is always an axiological core composed of values without whose minimum satisfaction the proposals and techno-scientific actions are simply rejected, as well as their results. Both the concrete values and subsystems have been emerging throughout history, have impregnated to a greater or lesser degree the scientific and technical actions and, thanks to their repeated interactions, they have been consolidating as such values or subsystems of values of the science. Faced with many philosophers of values that have tended to think of them as ideal entities, our axiology recognizes the historicity of values, their systemic character and, in addition, affirms the existence of emerging values in said systemic interaction. On the other hand, in the technoscientific activity there are transfers of values from other social activities to it, and reciprocally. This is one of the main ways of changing values in technoscience.

Everything we have been saying will be clearer if we enumerate some of the values belonging to the twelve subsystems that we have distinguished. By basic values we understand those that are common to human beings, although in some cases the origin of these values in the animal world could be traced. To clarify what we are talking about, use the following list, for whose presentation we resort to the alphabetical order, in order not to enter into the tremendous debates about the priority of one or other basic values:

1.- Basic values: joy, love, well-being, ability, sanity, creation, growth, happiness, fertility, strength, fortune, strength, joy, greatness, interest, maturity, need, normality, permanence, pleasure, power, prudence, neatness, health, safety, good sense, seriousness, sympathy, luck, survival, life, etc.

In this first enumeration the lax sense in which we apply the concept “basic value” is clear, since we include values, virtues and goods in the list, independently of the fact that these three concepts can be distinguished 210. Many of the mentioned values are strictly subjective, others no. Some are relevant to technoscience, others less. Our purpose is to illustrate through the examples the concept of “basic values”, since in this work we will not try to elucidate it. These observations also apply to the following enumerations, including the most significant characteristic of the sphere of values: the existence of opposites, that is to say of disvalores. It is important to keep in mind that values have their opposite, or disvalues. and that the evaluative or axiological rationality is based on the rule of increasing the degree of satisfaction of positive values and diminishing that of negative values, as we will see in the following section. Several of the terms that we have included appear in the list due to the relevance of the corresponding disvalue for human beings (sadness, hatred, discomfort, disability – or disability – madness, destruction, unhappiness, infertility, misfortune, weakness, suffering, smallness , disinterest, immaturity, abnormality, volatility, displeasure, impotence, imprudence, filth, illness, insecurity, insanity, irrisoriness, antipathy, misfortune, annihilation, death, etc.) and the same will happen with the other types of values that we are going to mention within each type.

2.- Religious values: authority, charity, devotion, divinity, hope, faith, grace, hierarchy, mystery, obedience, piety, purity, respect, sacredness, sacrifice, salvation, holiness, supernaturality, etc.

3.- Military values: authority, duty, discipline, fidelity, hierarchy, heroism, honor, loyalty, magnanimity, command, obedience, patriotism, peace, secret, courage, victory, triumph, etc.

4.- Moral values: altruism, friendship, autonomy, benevolence, good, kindness, compassion, duty, dignity, fidelity, happiness, generosity, gratitude, honesty, cleanliness (in the sense of fair play), prudence, respect, responsibility, sincerity, solidarity, tolerance, truthfulness, virtue, etc.

5.- Aesthetic values: harmony, beauty, clarity, correctness, creativity, delight, elegance, balance, grace, lightness, neatness, originality, simplicity, sublimity, subtlety, etc.

6.- Social values: seniority, cooperation, diligence, stability, excellence, success, fame, fraternity, gender, equality, privacy, freedom, merit, nobility, order, peace, prestige, privacy, professionalism, roots, recognition, security, solidarity, etc.

7.- Political values: autonomy, authority, control, democracy, stability, hegemony, governability, equality, independence, justice, freedom, majority, order, peace, power, power, prudence, public (res publica), representativeness, respect, tolerance, etc.

8.- Legal values: autonomy, clarity, fairness, formality, durability, stability, guarantees, impartiality, independence, justice, legality, legitimacy, freedom, publicity, representativeness, security, transparency, universality, etc.

9.- Economic values: benefit, quality, marketability, competitiveness, cost, development, efficiency, generosity, freedom, maximization, property, profitability, wealth, etc.

10.- Ecological values: biodiversity, conservation, equilibrium, cleanliness (no pollution), minimization (of environmental impacts), renovation, sustainability, etc.

11.- Technical values: applicability, competence, correctness, durability, efficiency, reliability, flexibility, functionality (in the sense that something works), skill, innovation, integrability (or compositionality), speed, robustness, simplicity (of use), utility, versatility, etc.

12.- Epistemic values: adequacy (empirical), clarity, coherence, contrastability, fecundity, generality, ingenuity, intelligibility, originality, precision, publicity, repeatability, rigor, simplicity, truth, verifiability, verisimilitude, etc.

As can be observed in these lists, several values are trans-systemic, because they can be considered from different meanings. None of the enumerations is intended to be complete and more than one inclusion is debatable, as well as the assignment of some values to one or other subsystems. We do not affirm the existence of types of fixed and immovable values, since, as already mentioned, the values are transferred from one social subsystem to another. Put another way: there is no “natural” typology of values. By classifying them in this way we are carrying out an axiological, or rather meta-axiological, action. It is not about proposing an immovable table of values. We intend above all to show the enormous variety of axiological issues that, with greater or lesser frequency or relevance, arise in the techno-scientific activity and, of course, also in other social activities. Some of those values (or virtues, or goods) are strictly subjective, others not. Therefore, our proposal could be refined and improved by introducing other criteria. Even so, the distinction of twelve subsystems of values relevant to technoscience is extremely useful for axiological analysis, apart from introducing a principle of clarification in a subject of enormous complexity. As for the order in which the twelve subsystems have been proposed, it could be modified. We have put the epistemic and technical values in the last places of the list on purpose, last but not the least. Initially, the value systems that have traditionally exhausted reflection on values (basic, religious, moral and military values) have been placed, but not because we consider them as the main ones for technoscience, but because they maintain a certain historical order. Even so, we have already said that ecological values, which should not be confused with moral values, no matter how much we talk about environmental ethics, have been the last to be configured as a system. Its impact on techno-scientific activity is still scarce, at least in some scenarios, but it is growing, so they should be considered as a specific subsystem.

After this brief presentation of what we consider as potential values of technoscience, it is interesting to underline the “ontological” assumptions from which we started 211. We consider values as functions (in Frege’s sense) applied to systems of actions by different evaluating agents. , obtaining as a result of the action of evaluating a valuation, and in some cases a judgment. Said in classical philosophical terms, which we will not normally use: the “faculty” of valuing is much broader than the “faculty” of judging. For this reason, the evaluation context is much broader than the justification context of Reichenbach and the positivist philosophers. The latter were only interested in epistemic justifications. This does not work for technoscience. Many techno-scientific actions are justified on the basis of economic, political, military or social criteria. Epistemic values are important, but they have lost the monopoly of the “justification” of scientific-technological activity. It is another reason why the classical philosophy of science is not valid to analyze and reconstruct technoscience.

V.3: Application of evaluation matrices to techno-scientific practice.

In the work Science and Values we introduced the notion of the evaluation matrix as a basic instrument for the development of an analytical, empirical, formal, pluralist, systemic and meliorist axiology 212. This axiology is based on the existence of a plurality of values that govern the scientific, technological and techno-scientific actions. These values are not a simple list, but are organized into systems and subsystems. That is why we can talk about epistemic, technical, economic, political, military, social evaluations, etc. In general, we can speak of a system V of values relevant to the techno-scientific activity, V = Vj, where Vj represents one of the twelve subsystems of previous values, so that Vj = vjk. Each value of the previous list, vjk, is applied to technoscientific actions to evaluate them based on very different estimation criteria. Since in these actions we had also distinguished twelve components, A = Ai, the action of valuing is represented in general by the axiological expression vijk (Ai), which can be a value statement or judgment (the scientist Ai is competent, the Ai instrument is accurate, the Ai theory is plausible, etc.), but also a number or score, when standardized protocols and evaluation scales are used, or, in the most frequent case, a preference or option for an alternative versus another: the scientist Ai has a better curriculum than Bi, the engineer Ai is more competent than Bi, the instruments Ai are more accurate than the Bi, the theory Ai is more general than the theory Bi, etc.

As we already indicated in the book Science and Values, in which the peculiarities of the evaluation matrices are widely discussed, inequations are the most usual representations of valuations: vijk (Ai)  vijk (Bi). This expression means that component j of action A is preferable (or better) than the corresponding component of action B, based on the vijk endpoint. Since the evaluations of technoscience are processes that take place in time, not specific judgments, the axiological inequations adopt the general form vijk (Ai (t))  vijk (Bi (t)), which represents the situation of preference for a proposal or techno-scientific action at a specific moment, always in relation to the vijk criterion. This does not imply a definitive assessment, since nothing prevents that at a later time Bi is preferable to Ai. An article sent to a journal can improve in a second writing, like the formation of a person, the presentation of a research project or the quality of an institution. Our axiology is melioristic, since it locates the advances or improvements in relation to each valuation criterion: greater precision, greater efficiency, more profitability, less economic costs, lower environmental impacts, better social reception (or in the market), greater competitiveness, etc. The axiological inequations that we have proposed allow us to represent the different evaluation situations, and this for the different values (or disvalores) that we are considering.

When, instead of considering a single vijk value, we take into account several evaluation criteria, it is necessary to introduce an additional parameter to represent the weighting factor pijk that the evaluating agent assigns to each of the vijk values. If all the values were equalized, the evaluation matrix would be: (vijk (Ai (t))). As this does not happen in real evaluative practice, but there are more and less relevant values in the opinion of the various evaluating agents, the most general form of evaluation matrices is: (pijk .vijk (Ai (t))). That is to say, it is a sequence of matrices closely linked to each other, a matrix. To give an example: this formal expression would represent all the value judgments issued over a time interval by a determined evaluator E that applies the vijk valuation criteria to the Ai component of a techno-scientific action. Throughout time there may be changes of criteria in the same evaluator. Some will consider this as a serious inconvenience, but they are wrong. The relevant values for the scientific practice can change, and in particular their respective weights. The important thing is the dynamics of evaluation, not the metaphysical belief in the timelessness of values or their eternal hierarchy. Axiological changes form an important part of the dynamics of technoscience, although these changes only affect the relative weights, not the system of values itself.

On the other hand, the evaluator E can be a scientist, an engineer, an entrepreneur, a merchant, a general, a politician, a jurist, an ecologist or any citizen. You can also be a bishop, a professor of ethics or an expert in aesthetic matters. To the extent that action A affects the lives of people, the evaluator E will be a normal person, that is, a user, or if someone who cares about the consequences and risks is preferred over him, his family or its environment could have the techno-scientific action A. Our axiology is not only pluralistic because it recognizes the existence of a plurality of values, but also because it starts from a plural agent, that is, from a plurality of agents more or less integrated in a system concrete techno-scientific Conflicts of values are inherent to the techno-scientific activity. This does not imply that we opt for the subjectivist theory of values 213. The question is more complex, or if you prefer more plural. There are subjective, intersubjective and objective evaluations. All of them have to be taken into account by the axiology of technoscience. Objectivity and subjectivity function as epistemic values, so they are part of a concrete subsystem of values. In addition, like the vast majority of values, they are gradual. There are irrational subjectivisms, others based on subjective reasons, others where there is a considerable degree of intersubjectivity (for example in cultural values) and we can also speak of other valuations that, being subjective in their origin, have finally been recognized as objective. Reciprocally, there are greater or lesser degrees of objectivity. Our axiology is based on the graduality of the values and this includes the concepts of objectivity and subjectivity, when they are used as a criterion of evaluation, which frequently happens in the techno-scientific activity.

The difficulties for the axiological-formal analysis of technoscience arise when we admit the existence of a plurality of evaluating agents, not only of a plurality of values. Many of them can be solved. In any case, the axiological functions of which we speak are not timeless entities or devoid of subject that applies them. The important thing is to clarify what are the shared values, especially if they come to constitute an axiological system, as is the case of technoscience. Although the different evaluating agents rank the values differently, that is, although they do not weigh them equally, they can arrive at common evaluations, whose results are intersubjectively accepted. In the case of technoscience (unlike science and technology) this happens even with heterogeneous agents, which represent and embody the subsystems of values of different social groups. We deal with situations that can be conflicting, and not only from a discursive or argumentative point of view, but from the perspective of the action. Not only are there opposing judgments, but also opposing actions. It is necessary to represent the evaluation processes, not just the specific assessments. Throughout a process of evaluation, shared value systems can be formed, notwithstanding the fact that tensions continue to exist. When a situation of axiological consensus is reached, standardized evaluation protocols and systems of procedural rules can be created to settle disagreements. This happens again and again in the techno-scientific practice, in which the rule of unanimity does not rule, much less that of the universality of Aristotelian science. The prior acceptance of procedural rules and, in many cases, the adoption of standardized evaluation protocols, is part of the evaluative rationality. In the following section we will see how these intersubjective evaluation protocols can be considered as specific evaluation matrices.

We have mentioned some of the difficulties encountered by the axiology of technoscience. To face them, it is necessary to have a more refined and precise conceptual framework than what has been said up to now. Let’s see it in more detail.

(a): First, it must be emphasized that the formal expressions we are using are valid for any axiological action: value judgments, preferences, choices, rejections, indecisions, etc. Although the evaluation criteria of agents E will vary a lot, and will usually be opposed to each other, the formal representation is the same for all of them. The evaluation matrices allow the introduction of a common protocol for the various assessments, which allows the comparison between them, however heterogeneous they may be. Above all, they allow detecting the existence of shared values, although the respective weights are different. When a set of shared values becomes stable throughout various evaluation processes, which is detected by analyzing scientific practice, the axiology can affirm (hypothetically) the consolidation of a system of values V, whose structure and modes of application must be analyzed. Said system V is one of the structural components of the corresponding techno-scientific “paradigm”, insofar as it guides the evaluation actions.

(b): Second, our axiology is based on the notion of satisfaction. When the evaluating agent E uses the vijk criterion to evaluate the component Ai of a techno-scientific action (for example, the results derived from it), what it does is to determine whether Ai satisfies or not the vijk value, and in its case in which case degree satisfies him. To the question: does Ai satisfy the vijk valuation criterion? Evaluator E can only respond in some cases “yes” or “no”. On such occasions the evaluation vijk (Ai) can be represented by “1” or “0”. We would be using a cardinal scale to represent the result of the evaluation by numbers. In other cases, the evaluator E is able to elucidate the degree to which, in his opinion, the component Ai satisfies the value vijk, or its disvalue vijk. This is what happens when someone awards a score to the vijk value. In this case it can be said that vijk (Ai) = gijk, where gijk is the assigned score, that is, the degree to which Ai satisfies the vijk valuation criterion in the judgment of an evaluator E, which can be individual, collective or institutional. This is the case, for example, when a teacher qualifies from 1 to 10, when a citizen completes an opinion poll, when a referee scores an article sent to a scientific journal or when a contest between large techno-scientific companies is resolved to award an important contract . This procedure is the most usual in the evaluation practice and allows to represent the results of a valuation action in ordinal scale.

However, at other times the evaluation has greater precision and can be represented on a scale of intervals or even on a metric scale (with a unit of measurement). This is very common when assessing scientific instruments, economic costs, impact rates or the price of a techno-scientific product in the market. In such cases the valuation vijk (Ai) is represented by a number and can be operated with it. The evaluation matrices are matrices in the mathematical sense of the word, so that various algebraic operators can be introduced to operate with the estimates made by E and other evaluating agents. This is where it makes full sense to talk about weights. For this reason we will reserve the expression pijk.vijk (Ai) for situations in which scales of intervals or metrics 214. can be used. In such situations, for example, it is possible to find the arithmetic mean of the evaluations issued by different agents, as well as to introduce other mathematical and statistical operators. The procedure for resolving the differences in valuation can also be instituted by referral to a third instance, for example a higher ranking arbitrator. Or, what is more frequent, the two alternative proposals can be promoted, leaving it to be time, the market or society who grant their favor to one or the other. This is usual in the phases of product development and commercialization. The higher level of penetration or sales of various techno-scientific innovations, once placed on the market, works as a rational criterion for conflict resolution. It is not the only procedure, of course.

The axiology that we advocate is formal, or formalizing, and adopts mathematical and computer-based representations without problems. Valuations E (pijk.vijk (Ai)) do not have to be represented only by value judgments, as in natural languages, but also as magnitudes, using different scales of measurement. By empirically analyzing the evaluation processes, agents and scenarios where conflicts between alternative proposals are resolved are also detected. The scientific and technological communities are one of those scenarios, but not the only one, and in most cases not the most important one either. The technoscience assessment criteria are mixed. Scientific communities were those that formerly determined what is acceptable in science and what is not. With the emergence of technoscience, they continue to play a role in this respect, but they do not have a monopoly on evaluation. Put another way: the evaluation context of technoscience is inter- or trans-communitarian. The military, businessmen and politicians introduce new evaluation criteria, in addition to the epistemic and technical ones. The society and users of techno-scientific devices also have an important role in the evaluation processes of technoscience. For the defenders of the autarky of science, grouped under the slogan that only those who know science (or technology) can value technoscience, this produces scandal. However, it is a necessary consequence of the structure of techno-scientific practice, and more specifically of its axiological structure.

(c): Third, the divergences between the evaluating agents are the rule, not the exception. That is why we say that the subject (or agent) of technoscience is plural. The generation of shared value systems, the processes of consensus and the establishment of procedural rules to resolve differences and conflicts, if necessary before courts, are some of the most relevant issues for the axiological analysis of techno-scientific activity 215. usually it happens that the proposals overcome some phases of the axiological screening, but not the rest. For example, a research project can be very well posed from the scientific and technological point of view, but it can be rejected later because it has no military, business or commercial interest. The evaluation processes are iterative: that is why we speak of axiological screens. The techno-scientific proposals are passing successive thresholds of valuation, but they have to pass them all to become effective. Each evaluating agent incorporates its own criteria and can differ completely from other agents that had considered an appropriate proposal to be excellent. The axiological pluralism entails a sequentiality, with feedback between the various phases of the project. Although we represent the whole process through an evaluation matrix, in reality we have to distinguish several sub-matrices, each of which expresses the diversity of value systems that intervene in technoscience.

(d): Fourth, the axiology that we advocate, because it is empirical and formalizing, is not limited to locating the various evaluating agents over time, but also clarifies and makes explicit the values actually used in these evaluations. To the extent that standardized protocols and evaluation matrices (or derivations of such formal instruments) are used, the final results of the evaluations can be analyzed and justified, including divergences and conflicts. Faced with the concealment of the real evaluation criteria, typical of subjective judgments, the evaluation matrices increase the degree of intersubjectivity, and in the best case of objectivity of the evaluation processes. Before proceeding with a valuation, each evaluating agent must publicly declare the criteria that he or she wants to apply, and, where appropriate, also the relative weightings. As a result of this pre-evaluative phase, the evaluative action is subject to rules, like any action, instead of being governed by the free will of each evaluator or of the one with the most relative power. Evaluation matrices, when applied, contribute considerably to the normalization of evaluation processes, increasing the degree of objectivity of their results. Of course, the evaluation processes are not linear, as we already pointed out. The possibility of using the results of an evaluation, of having it repeated with different agents, etc., improves the evaluation processes and their results. All this introduces an important legal component in the techno-scientific activity: the performance of the evaluation committees must be subject to rules, and in the case of public actions also to laws. The same applies to the registration of patents or lawsuits that techno-scientific companies may have among themselves. Judicial bodies are the last link in an evaluation process, but no less important.

(e): Fifth, the axiology of technoscience based on the use of evaluation matrices favors criticism and intervention. It is enough to compare, for example, two evaluation matrices used by two evaluators E and E ‘to detect absences and axiological biases in the practice of both. This applies to individual evaluators but also to evaluations carried out by groups, commissions or institutions. The indicators of scientific-technological activity are only one of the expressions of what we call evaluation matrices here. They are usually economic (spending on R & D), professionals (human resources available), bibliometrics, patented and technological innovation. Recently, social indicators have been introduced (RICYT 2001). The absence of ecological, legal or ethical indicators show the defective structure of the evaluation matrices effectively used in said processes. When analyzing the evaluation criteria effectively used, as well as their respective weights, the criticisms cease to be ideological and become formal improvements. Of course, the proposed improvements have to specify the values to be included and the weights that must be modified. The controversy and the debate take place before evaluating, which improves the evaluation techniques and increases the degree of intersubjectivity and objectivity of the assessment instruments that are going to be used. Put another way: the evaluation criteria themselves that are going to be used have to be evaluated, both ex ante and ex post. This improves axiological actions, by perfecting the instruments with whose help they are carried out. Do not forget that we consider valuations as actions and, therefore, subject to the theory of action that we have mentioned repeatedly. In our view, the evaluation matrices and their derived developments suppose a considerable improvement of the technoscience evaluation processes. This does not prevent those instruments also have shortcomings and shortcomings. The important thing is to institute the principle of meta-evaluation (or control of evaluations), according to which one must evaluate the axiological actions themselves, and therefore their agents, their instruments, their initial conditions and contour (for example, pressures to the evaluation committees), their results, their consequences and their rules. Formulating prior procedural rules for evaluation processes is one of the net improvements to be considered, because it reduces the degree of discretion of the evaluators. Observe that what we are saying does not contradict our previous acceptance of a certain degree of subjectivity in the evaluations of techno-scientific activity. Subjectivity in evaluations can reach a certain degree, but it must never be the dominant criterion. The subjective assessment could even be weighted, combining it with the remaining assessment criteria. The important thing is that this weighting factor was explicit and prior, instead of being implicit and manifested in times of conflict, as is often the case. When hiring researchers, for example, the letters of support that the candidates receive from scientists, personalities or prestigious institutions are usually weighted. This is a factor to be taken into account, not the only one. Properly weighing these subjective judgments is part of the construction of an evaluation matrix.

(f): Sixth, evaluation matrices are very useful when comparing different techno-scientific areas and systems, favoring the transfer of values between them and the axiological change in broad areas of technoscience. Let’s take a very trivial example: the degree of computerization of the techno-scientific practice itself, whether in the context of research, application or education. Or even in the context of evaluation, which is an indicator of great relevance to analyze the evaluation practice. Or also: the percentage of the Gross Industrial Product that some countries dedicate to scientific-technological research, or to education, or to innovation. If a country compares its investment in R & D with that of another country that is more technologically advanced, it can reshape its budget policy and set the objective of gradually increasing this percentage of investment in R & D. The same applies to the priority value: priority lines are quickly imitated by other countries or techno-scientific agents. From our perspective, this transfer of values would be facilitated and specified with the systematic use of evaluation matrices, regardless of the format they adopt in each case. What is said is not only valid for public technoscience, but also for private technoscience. The matrixes would also allow to compare both types of technoscience, with all the consequences that would derive from it.

(g): Seventh, it should be emphasized that evaluation matrices are not proposed in order to try to define deterministic algorithms for decision making nor are they based on the maximization of utility functions 216. Except in very exceptional cases there are no such algorithms 217. One of the main reasons is that axiology usually works with ordinal scales and inequations. Our proposals are inserted in the line of work initiated by Herbert Simon, based on the notion of satisfaction versus the maximization of values and constitutive of what is now called bounded rationality. In general, each value vijk or disvalor vijk have associated a minimum level cijk of satisfaction of a positive value, below which it is said that the techno-scientific proposal is rejected, and a maximum level of dissatisfaction of the disvalue, Cijk, above of which the proposal is also not accepted, for exceeding the maximum tolerable threshold of said disvalue. These levels may vary throughout an evaluation process, and in general over time, being one of the main indicators of the progress of scientific activity in relation to this value and disvalue pair. In formal terms, for a techno-scientific proposal or action not to be rejected, it is necessary that i, cijk  vijk (Ai)  Cijk, and that both at a given moment and over a period of time. The scientific theories themselves support a certain number of anomalies, as Kuhn showed, provided they are not excessive and provided that, in addition, these theories have a sufficient number of empirical tests to support their possible validity. A technological device can have a certain number of faults, or a foreseeable period of obsolescence, but if those disvalores are manifested in excess the corresponding device is replaced by another, or withdrawn from the market. This type of bounded rationality is the one that also prevails in political, social, ecological and military spheres, and even in legal environments, although in this case with a lesser degree of flexibility. Not so in economic circles, where the “maximizing paradigm” has been implemented with force, becoming even a model for the analysis of social action, through the theory of rational action. As we have already said, in economic valuations it is easier to use metric scales, due to the existence of money as a unit of measurement. This has generated a reductionist tendency: many theories of rationality have accepted the maximizing paradigm. However, even in economic theory there are strong tendencies against it, starting with Simon and ending with Amartya Sen. Regardless of the clarity, simplicity and utility that maximizing techniques may have in the social sciences, they are empirically inadequate and technically biased in the case of the axiological analysis of technoscience. On the other hand, the existence of minimum levels of satisfaction and maximum satisfaction is one of the “symbolic generalizations” most characteristic of bounded rationality. We will return to this question in later publications.

(h): In eighth place, we not only use the distinction between the twelve subsystems to analyze the axiological structure of technoscientific activity. We also distinguish between central and peripheral (or nuclear and orbital) values. By core or nuclear values we mean those whose dissatisfaction (vijk (Ai)  cijk or vijk (Ai)  Cijk) implies the immediate rejection of a component of a techno-scientific action, and therefore that of the action itself, until such a component does not be modified. There are core values in each of the twelve subsystems: for example, incoherence or lack of empirical adequacy (epistemic values), uselessness or dysfunction (technical values), disproportion or lack of profitability (economic values), indiscipline or cowardice (military values), etc. The peripheral or orbital values, on the other hand, do not entail the automatic rejection of the component or of the action, although they raise doubts about its suitability. From our perspective, the five values that Kuhn considered as permanent of science (precision, rigor, coherence, generality and fertility), are nuclear values of science. This does not mean that they have to be satisfied to the fullest. What is essential is that they do not fall below certain levels of satisfaction (changing according to values, situations and times), or that they exceed the maximum levels of tolerable dissatisfaction. In the case of science, the axiological core is composed exclusively of epistemic values. In the case of technology by technical values. To the extent that science and technology were involved in industrial production, axiological nuclei were transformed, giving entry to some economic and business values. In the case of technoscience this trend has become more acute, and in many directions. In general terms, we will say that the axiological core of the various technosciences always includes epistemic, technical, economic and political values, and very often military and legal values. Ecological values, today, are on the periphery of technoscience, as well as aesthetic, moral and religious values. This does not mean denying the existence of cases in which these values are nuclear, or could be, especially in some countries and cultures. As for the basic values, some of them are part of the axiological core of some technosciences (for example, the technomedicine), but not all. For example, the technomathematics is hardly affected by the basic values. In summary, the distinction between central and peripheral values is a formal distinction, whose effective concretion has to be investigated with case studies. It is not possible to affirm an axiological nucleus common to all technoscience modalities, although we should not rule out that this nucleus ends up being conformed as the technoscience develops and consolidates, as it happened historically with science and technology.

(i): Finally, it is necessary to clarify the notion of the value system of technoscience, V. So far we have talked about the various possible subsystems and we have just introduced the structural distinction between nuclear and orbital values 218. We have also affirmed that the system V values that govern a certain techno-scientific activity is never formed by a single subsystem (epistemic values, technical values), as was the case of science and technology. Of course, this also applies to other subsystems. No matter how militarized a techno-scientific activity may be, military values are never the only relevant ones. The epistemic, technological and economic values always have a presence in any techno-scientific activity, and not only in the periphery, but in the axiological center. Therefore, a V system is always a mixed system. Just as the techno-scientific agent is plural, because it is composed of a set of members, each of which represents, embodies and defends this or that subsystem of values, so the evaluation matrix that defines said system V is structurally heterogeneous, that generates the existence of submatrices within it. Each of the submatrices represents the nuclear values from each of the twelve subsystems we are considering, usually four or five. The same happens with the peripheral values, which are also organized by subsystems and are represented by submatrices 219. The V systems can be very different according to the different technosciences, contexts and situations. For example, they differ radically according to whether we are in the context of education, research or application. Therefore, each V system is associated with a field of techno-scientific activity, which must be empirically solved. These systems arise, develop and consolidate in the techno-scientific practice itself, generating in some cases stable V systems with standardized and generalized evaluation protocols. In such cases we will say that this activity is a mature technoscience. Although we have not said so far explicitly, both “scientificity” and “techno-scientificity” (if we are allowed the word) can be used as terms of value, and therefore are a matter of degrees. Macro-science is in an intermediate degree, or if you prefer, it was a transition from science to technoscience. The existence of V systems of values, stable, normalized and generalized in a scientific-technological system, as well as the integration into V of several subsystems of different values, express the degree of advancement and implementation of technoscience. If we apply the evaluation matrices to a specific technological system, it becomes possible to analyze the structure of the system V of values, and therefore part of the structure of the techno-scientific practice.

V.4: Technoscience and power.

One of the most marked characteristics of technoscience is its connection with various forms of power: economic, military and political, in particular. Although some authors, such as David Noble, have considered technoscience as a new religion 220, the truth is that the relations between technoscience and religious powers are rather scarce, if not conflictive. The current debate about stem cells is a good example of this. Religious values have an impact on technoscience, but usually in contrast to many of the techno-scientific innovations. What does happen, however, is the insertion of techno-scientific power at the very core of the traditional great powers. Entrepreneurs, politicians and the military, depend on technoscience to increase their power.

Numerous authors have studied from a historical point of view the progressive consolidation of the power of science and the establishment of links with other classical powers, in particular with military and economic power 221. For our part, to explain the emergence of techno-scientific power we will a more philosophical approach, introducing the notion of capacity for action, inspired by some ideas of Amartya Sen, Nobel Prize in Economics (1999) 222. His proposals in economics can be a good source of inspiration in philosophy of science, as he has pointed out J. Francisco Alvarez 223. In our case, we will not take them literally. We will freely reinterpret Sen’s thesis on the space of capabilities, in order to explain the continued increase in the power of technoscience throughout the twentieth century.

We will say that, just as science has increased the cognitive capacities of human beings, techniques have increased their action capabilities, using machines as body prostheses. The same can be said of industrial technologies, thanks to whose use enormously increased productive capacity, as well as energy capacity (electricity) and the means of transport of people and goods, making possible the appearance of large factories and metropolises industrialized The emergence of technoscience has meant a qualitative leap, both in terms of knowledge and action. Computers, radars, atomic bombs, particle accelerators, synthetic materials, spacecraft, artificial satellites, television, telematic networks and many other canonical examples of technoscience coincide in one fundamental property: they make possible actions that were impossible before. From this comes a first deep relationship between power and technoscience, to the extent that it affects the sphere of the possible. The nuclear winter is the clearest example, since, if it occurs, it would radically alter the face of the planet, including the disappearance of a large part of the human species and the radical transformation of the eventual survivors. Technoscience completely transforms the space of capabilities Sen speaks of. If politicians, the military and businessmen are interested in techno-scientific artifacts, together with the public that uses them, it is because these artifacts revolutionize the scope of what can be done. Technoscience places us before a space of radically new possible actions, both individually and collectively. The reason for the close relationships that have developed and consolidated throughout the twentieth century between macro-science and the great powers is that techno-scientific artifacts open up new capacities for action, and this at a qualitatively higher level than the technologies of industrial era.

With the advent of technoscience proper a new type of machines emerged, the infomáquinas, which allow to simulate and control the operation of various types of artifacts. Technoscientific devices operate primarily on other types of machines, automating and controlling their operation. This is clearly manifested in the case of new weapons, guided by remote telecontrol, but also in industry, by automating production, in trade, by enabling the purchase and sale through telematic networks and, finally, in the own society, when our offices and our computer equipment houses are populated. The manual operator has been replaced in many productive sectors by the computer operator, multiplying the rates of production and distribution. By directly influencing governments, companies, military organizations, the market and society, technoscience has modified the six major areas of SCyT systems that we distinguished in the previous chapter. Its success does not depend on the new scientific knowledge it has generated, but above all on the modification of human activity, which is increasingly dependent on a whole plethora of techno-scientific artifacts that are nowadays used daily.

The set of capabilities of a person can be defined as the set of possible and valuable actions for it, giving by understood the draft theory of action with twelve components that we have summarized in the previous chapter. As we saw when commenting on the definition of “technical realization” proposed by Quintanilla, the technical actions are closely related to what the technical agents consider valuable. Therefore, they are part of the space of human capacities, such as Sen 224 understands it. We will say then that, just as classical philosophers defined the human subject by their notes or properties, techno-scientific agents are characterized by their capacities for action, including the positive or negative evaluations of them, that is, the values and disvalores. As an agent, the human being has in each moment a set of action capabilities, valued by the subject, but not only by him, but also by the other agents that carry out similar (or opposite) actions. This capacity space is extended or reduced throughout life, depending on the states through which the agent passes. Human agents have an associated space of action capabilities whose actual or potential realizations not only depend on them, but on the other components of each action. The situations, the means and instruments with which they are counted, the possible risks or simply the initial conditions work as constrictions of that space of possible actions. Some of these components do not limit, but enhance the capacity for action. Such is the case when the agent-subject is inserted into a techno-scientific system and is competent in the use of the corresponding instruments. Reinterpreting Sen, we can say that, in this case:

1.- Possessing scientific knowledge (theories, facts, methods) is not only an epistemic good, but also economic, military, political, social, etc. From the perspective of the subsystem of epistemic values, having knowledge of the various scientific theories, a good curriculum and prestige as a researcher, professor, disseminator or professional of technoscience is equivalent to having epistemic assets. Scientists try to make theirs and increase those assets, because they provide them with epistemic well-being. However, this knowledge, once implemented technologically and applied to the market, is an undoubted advantage for those who own it, because its capacity for action is increased. The symbiosis between scientific knowledge and other social agents has radically transformed the system of epistemic values. These continue to exist, but they are systemically linked to other value systems. The interaction between the episteme and the polis brings mutual benefits. Knowledge remains an epistemic good but, in addition, it becomes intellectual capital. This was the great contribution of Vannevar Bush’s report.

2.- The instruments for research and large equipment are in turn technical goods. They are highly valued by scientists and engineers, because without them they can not act. The technological component of scientific research increases the capacity for scientific action, that is, the ability to compute, observe, measure and experiment. We will call technological goods to this component of the techno-scientific activity.

3.- For the techno-scientific entrepreneur, on the other hand, both the knowledge of the scientists he hires or finances and the skills and abilities of the technicians are first of all economic goods, which we must try to make profitable. In the case of public research companies, profitability does not have to be strictly monetary. The increase of knowledge or technological progress can also be profitable, due to its subsequent repercussions on society, health or the market. In the case of private R & D & I companies, the benefits are usually monetary, but neither are they the only ones: consolidation and expansion in the market, for example, is usually as much or more important than realizing benefits. . From our perspective, these strategic objectives are perfectly rational, by increasing the capacity of these companies to act. Having a certain market share means delimiting (or increasing) the capacity for business action: greater production, greater commercialization, greater economic activity, as they say. The scientists themselves are usually sensitive to this type of economic valuation, although it is not the main one for them. The financing obtained, the jobs available and the salaries that are charged are important aspects for techno-scientists, since they not only have epistemic or technological interests, but also economic ones. The sociologists of scientific knowledge have insisted a lot on the importance of the interests of scientists. They are right, but with a very important nuance: just as we have distinguished several subsystems of values relevant to technoscience, so we must distinguish as many meanings of the term “interest”, or the term “good”. The technoscientific goods and interests have many facets, given the plural structure of the techno-scientific agency and the value systems V that guide it.

4.- The same can be said of the military, who form a considerable part of the techno-scientific enterprise. Most military actions are today techno-scientific actions, at least in the most advanced armies, which coincide with those that have increased their capacity for action and intervention. These actions are also valued as assets by the strategists, or if you like as interests. The defense of the strategic interests of a country justifies a war, even preventive, like that of Iraq, not only in response to an aggression. The scientific-military lobbies promote techno-scientific research in order to increase the capacity of action of the armies, whether offensive or defensive. It is not its only objective, of course, but its high value of technoscience and its institutional imbrication in it come from the impact that technoscientific research has in the space of military action capabilities.

5.- Even with significant differences, the interest of politicians for technoscience has similar roots. Not in vain the leit-motif of political propaganda is: facts, not words. These facts are always the result of political actions, for which technoscience makes very important contributions. The Bush model of scientific-technological policy, as we saw, is based on the postulate that basic research and technological development are the great engines of progress in the politically strategic fields: security, economy, health, education, defense. Subsequently it was shown that the transfer of knowledge and technology is an excellent instrument for diplomacy. Technoscience is one of the great pivots of contemporary states, unlike the science of the seventeenth and eighteenth centuries, which played a subsidiary role. Therefore, the techno-scientific power constitutes one of the great powers of the State. Articulating a scientific-technological system that enables the development of this new form of power, as well as its balanced integration with classical powers, is one of the great problems of contemporary states. Technoscience is inserted in the hard core of political power, as it had previously done with military and economic power, because it is one of the main factors of transformation and control of societies, without prejudice to its domination over nature, which keep exercising. Put another way: its progress is a political good and is part of the interests of the State. That is why the scientific-technological policies are usually questions of State. The assessment that politicians make of technoscience is very different from that of previous techno-scientific agents, but no less positive for that. The evolution of contemporary societies throughout the twentieth century has shown that those countries that have promoted techno-scientific activity have acquired a much greater weight in the international arena, and this in the main areas of interest of the States. Therefore, it is chosen to promote and regulate it legally, according to different models that, yes, usually have a strong ideological and party component 225.

So far there are no doubts. As a whole, technoscience is a good, although there are preferences for some or other lines of research, depending on the respective interests and values. We have already said that, although it is mainly developed by scientists and technicians, the techno-scientific activity is always supported by other social agents that are integrated into the science and technology systems in order to enhance their own capacities for action in the market, society, international relations and battlefields. Jurists also participate in the SCyT system, even if it is subsidiary. Simplifying a lot, we could say that, for all these techno-scientific agents, own technoscience is always a good (at least at the beginning) and therefore it must be promoted and developed. The notion of well admits very diverse meanings, as we have already mentioned. Conflicts of values arise because each agent promotes its own conception of the good, without there already being a supreme good to which the various subsystems of values are subordinated. In general, these principles are usually resolvable through agreements and multiple transactions, which are established in the techno-scientific practice itself. The threats come from the technoscience possessed by the enemy, opponent or competitor. If it is better, either you have to make it your own or you have to improve it. The competition between armies, companies and States is the main engine of technoscience. Since, generically speaking, technoscience increases the capabilities of action (business, political, military), to overcome the adversary it is necessary to overcome it in techno-scientific development. The fundamental principle of technoscience, as we saw in chapter 4, is pragmatic: it is the source of economic, political and military progress. It is not a law of nature, but a principle for strategic action in a competitive framework.

In other words: technoscience generates power because it increases the diverse capacities of action. Since, in philosophical terms this time, increasing the capacity for action is good, technoscience is a business, political and military good. The main good is not knowledge, but the capacity for action. We are simplifying a lot, but thanks to this we can contrast the basic principle of modern science, the knowledge (and domain) of nature is a good, in front of this new basic principle of technoscience. The search for physical-natural or other knowledge has not ceased to be a good: technoscience is based on science. But the difference is radical, since now this increase in knowledge, including basic research, is only a means to increase the capacity for action, in this case political, military and business. With this we come to one of the conclusions of this book: knowledge is a means to action, not an end in itself. For that reason, philosophical theorizations about the goals of science are not valid for technoscience. The philosophy of science has to change because science has changed, and in particular its objectives. Even the endless search for truth, to remember the venerable Popper, becomes an instrument to increase the capacity for action. This is the reason why we have been insisting that the philosophy of science should focus on scientific activity, rather than on knowledge. If there is one, which will have to be studied in depth, the rationality of technoscience is practical. 

Therefore, it is essential to choose one or other models of practical rationality, but not in the ethical sense of expression (although ethics also plays an important role in studies on technoscience), but in the sense of rational action. We have already expressed our criticisms of the instrumental conceptions of rationality, which are still valid in technoscience (knowledge is a means), as well as our option for evaluative or axiological rationality. The debate on this will be long and this option for bounded rationality versus the maximizing rationality of the rational decision theory is a first step in that direction.

But what happens with the other six subsystems of values, of the twelve that we have listed, and with their corresponding axiological agents?

Problems and conflicts already existed among the promoters of technoscience, but at the end of the 20th century they have become more acute. If we take into account the representatives of social, ecological, aesthetic, religious or moral values, and much more to the representatives of basic values, which are people in general, it is logical that conflicts of values manifest more frequently. For these social sectors, undoubtedly majorities, it is doubtful that technoscience is a good. In many aspects it is an evil, because it transforms them, sometimes positively, but sometimes negatively. In any case, the six types of agents remaining are much more attentive to the consequences and risks of techno-scientific actions than to the immediate results of them.

The reasons why this happens are not conjunctural, but structural. Let’s see some of them:

6.- As far as the societies are concerned, it is logical that concern should arise, because we must not forget that the transformation of societies is one of the main objectives of techno-scientific activity, unlike modern science and technology. industrial. The new information and communication technologies (ICT) are a good example. ICTs generate a new social space (the electronic space, or third environment) in which a new form of society, the information society and, for some, of information and knowledge can be formed and developed 226. ICTs are producing tremendous impacts on societies, not only on politics, armies or companies. Being one of the current paradigms of technoscience, since they have radically transformed the actions of scientists and engineers, ICTs show the extent to which technoscience is oriented towards the transformation of societies, not of nature. The same could be said of advertising technologies, pharmacology, design drugs or cognitive technosciences (or knowledge engineering, such as robotics or artificial perception). It is about transforming people and societies. It is not surprising that the transformaturi have something to say about it. From this structural conflict arise numerous social movements of criticism to technoscience, starting with the CTS studies in which this book is located. From a philosophical point of view, one of the central problems is risk. In the first place, dangers derived from errors in techno-scientific actions, whose consequences can be catastrophic, because technoscientific devices control the operation of many other systems and machines227. Second, as a clash between the techno-scientific culture and other cultures.

The technoscientific power is separated from society and can hardly be controlled by it, because the current control procedures are mostly techno-scientific. From this conflict arises a permanent tension between the freedom of techno-scientific research, which tends to be conceived as an unlimited freedom of action, and the social control of technoscience, for which there are no effective mechanisms today, given the strategic alliance that techno-scientific companies have established with political power. For this reason, movements for the democratization of science (Budapest Declaration of 1999) emerge, which should rather be called democratization of technosciences. Techno-scientific power has been closely linked with traditional economic, political and military powers. It is not surprising that counter-power movements arise, above all because of the scarce presence that, today, social values have in techno-scientific activity. It is not our intention to address these issues in this book, because our aim has been to analyze and clarify the concept of technoscience, but we do not doubt that this will be the main structural problem of technoscience in the coming decades. The presence of users of technoscience in the instances of evaluation, design and decision making is, in our opinion, a first step in this regard.

7.- The same happens with the ecological values and the axiological agents that advocate them. Although one of the main differences between science and technoscience lies in the latter’s willingness to intervene in societies (will to power, it could be said in Nietzschean terms), this does not prevent technoscience from maintaining the classic objectives of science and modern technologies. In this regard, biotechnologies are the canonical example (transgenic foods, genetic engineering, cloning, artificial reproduction). But we must not forget the devastating effects of some techno-scientific actions on the environment as a whole (nuclear waste, Chernobyl type accidents, threat of atomic war, greenhouse effect, etc.). The actions of numerous NGOs (such as Greenpace), summits such as Rio (1992) or the recent one in South Africa (2002) and, above all, innumerable small actions in defense of the environment, must also be considered as technoscientific actions, although the they carry out agents located in the periphery of the SCyT system that defend values that are not yet in the axiological core of technoscience.

8.- The aesthetic values and the social agents that promote them (artists, architects, filmmakers, models, singers, musicians, some sportsmen, videogame designers and Web pages, etc.) are rapidly entering the techno-scientific activity. We can talk about techno-art in this case, as it is one of its usual names, without forgetting the scientific component of the new instruments and artistic formats. Some creators of science fiction, coming from the counter-cultural movements of the 70s, have had a very important anticipatory function. From an aesthetic point of view, cinematographic images like those of Hal, Blade Runner, Robocop, Terminator or Matrix, to name some of the most famous, have perfectly reflected some of the aspects of technoscience, precisely the most worrisome. We should also write the artistic history of technoscience throughout the twentieth century, but not having knowledge or competence for it, we just point to this possibility, which, to the surprise of some, would become part of the studies on technoscience , in this case artistic studies. All the speculation about cyborgs, promoted at times by avant-garde artists, is an excellent example of the presence of aesthetic values in techno-scientific activity. In some cases, this presence is peripheral, in others it is not. There are branches of technoscience, for example scientific visualization, or video games, where aesthetic values are part of the axiological core, always along with other types of values:

 

technological, economic, socio-cultural, scientific and even military (or rather warrior), at least if one takes into account the heavy burden of violence of most of these techno-images.

9.- In general, religious values clash strongly with technoscience, especially in those countries where there has been no separation between religious power and state power, or in those cultures where the dominant power remains the religious, as is common in many areas of the Third World. The holders of religious power, especially if they hold it absolutely, see in technoscience an enemy to fight, if not the devil or the incarnation of the evil that their respective mythologies have produced. Therefore, far from being integrated into the scientific-technological-political-military-business alliance that is at the origin of technoscience, religious powers tend to fight against it, or at least deeply distrust it. They have good reasons for this, since we have already said that technoscience arises to transform societies and religion is a basic component of almost all social structures. These conflicts are minor in countries where there are non-denominational states, and especially in those where religious activity takes place mainly in private or intimate areas, but they do exist. Techno-scientific power is a dangerous adversary for religious power, as it was once enlightened scientists. The analysis of this type of conflict would make it possible to fine-tune these quick comments that we are making here.

10.- We come to ethics, or moral philosophy. It may seem disappointing, but we will say little about it, since, as we have already said, axiology covers a much broader field than ethics. As regards the presence of moral values in techno-scientific activity, it does occur, but in no way in the axiological core, except in exceptional cases. In general, ethical assessments of technoscience are secondary, or subsidiaries. It is true that very serious problems of conscience arise in some scientists (the Punjab movement that opposed the atomic bombs is a good example) and that, as in any human activity, ethical issues arise continuously (honesty, friendship, enmity, dignity, duty, etc.). But technoscientists usually fix themselves with specific deontologies, following the example of Hippocrates and the medical profession. There are exceptions, of course: bioethics is one of them, as manifested in the fact that Bioethics Commissions have been created in the hospitals of the techno-scientifically developed countries, or also in the existence of Committees and Foundations of Bioethics and Infoethics. But when we talk about the Genome project of the ELSI project associated with it, the budget weight that was assigned to the ethical, legal and social aspects of the Genome Project was 5%. This gives a clear idea of the relative low weight that these issues have when investigating the consequences of large techno-scientific research projects from a moral or social perspective. Technomedicine is one of the technoscience modalities where applied ethics can have a nuclear presence, but even in this case the technological, scientific and economic values prevail over the strictly moral ones. Once again we are faced with an issue that deserves a more in-depth study, which we can not undertake here.

11.- Finally, we will briefly talk about the basic values and the conflicts they generate in technoscience. This is another of the central problems, although here we will devote a very brief attention.

Summarily stated, what is at stake is the technification of people, not just their way of life, because this has already happened. Health and pleasure are increasingly mediated technologically, not to mention entertainment, joy, pain or feelings, which have their best field of expression and development in television, advertising, phones, video games and the Internet. The convergence between various mentioned technologies, such as those just mentioned, implies the emergence of a new social space, whose functioning and development is strictly mediated by these technosciences. Apart from agrarian societies and large metropolises and industrial states, information and communication technosciences enable the emergence of a new modality of person, the e-person or electronic person, understanding the term “person” in its etymological sense of mask. The society of information and knowledge implies a radical transformation of the human being. In addition to the physical and citizen identity, people are acquiring a third identity, the electronic identity. Techno-scientifically marked by chips and access codes, the transforming power of technoscience is reaching the ultimate components of societies. In this case, too, the predominant values are those that make up the axiological core of technoscience, and first of all the technological and economic values, not to mention the military values, which run at ease through a large part of the electronic space. In the new social space there is no constituted political power. Therefore, we consider it as the techno-scientific space par excellence. In the absence of polis, there are no citizens, only customers, users and consumers.

In our view, this is a third phase of the techno-scientific revolution of the twentieth century. Its evolution will mark the main social transformation of the 21st century.

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English Translation of COLCIENCIAS Project Typologies version 5

English Translation of COLCIENCIAS Project Typologies version 5.

Available here Tipologias de Proyectos version 5 2018 or on COLCIENCIAS.

  1. General Definitions.

Actor Recognized by Colciencias: Are those natural or legal persons that are susceptible of recognition by Colciencias as established in the policy of recognition of actors and that are enabled by the tax statute to give endorsement to a project that is presented to the call for tax benefits.

Scope of the project: i) The scope of an investigation indicates the goals that must be met or the results that will be obtained from the execution of the project and conditions the method that will be followed. ii) It is the work done to deliver a product, service or result with the specified functions and characteristics3

Social appropriation of science, technology and innovation: The Social Appropriation of the CTeI is an intentional process of understanding and intervention in the relationships between science, technology and society, which aims to expand the dynamics of generation, circulation and use of scientific knowledge -technological, and promote synergies between academic, productive, and state sectors, actively including communities and interest groups of civil society. It must include in a comprehensive manner the following components: Citizen participation in CIII, Communication of CIII, Exchange and transfer of knowledge, and Knowledge management in Social Appropriation of CIII.4

Guarantee: In the case of projects for tax benefits for investment, the guarantee must be given by the legal representative of the actor recognized by Colciencias. In any of the cases, the recognition must be valid at the time of making use of the tax benefit and it will be understood as official with the signature of the letter of presentation, endorsement and acceptance of commitments presented in the call.

The endorsement implies that the recognized actor is linked to the project with the role of Co executor or technical supervisor and is required to begin the evaluation process of the proposal.

Project life cycle: “It is the series of phases through which a project goes from its inception until it’s closure. (…) The phases are bounded in time with a beginning and an end or point of control. “5

Science, Technology and Innovation (CTeI): The qualification as technology and innovation science projects, hereinafter CTeI, includes the qualifications established in the law as “scientific, technological or innovation”, “research and technological development” projects or “of high content of scientific and technological research” as well as the other references in this matter contemplated in the current legislation.

Contingency: An event or an occurrence that could affect the execution of the project and that can be taken into account as a reservation.

Counterpart: These are the resources contributed by income taxpayers for the realization of a Science, Technology and Innovation project that will access tax benefits. The counterparts can be in cash or in kind (when a cash payment is not made for the development of said activities).

Copyrights: “They are the rights of the creators on their literary and artistic works. Works that lend themselves to copyright protection range from books, music, painting, sculpture and films to computer programs, databases, advertisements, maps and technical drawings. “7

Industrial design: “It is any external form or aesthetic appearance of functional or decorative elements that serve as a pattern for its production in industry, manufacturing or crafts with special characteristics, so that they add value to the product and generate differentiation and variety in the market. . The protection modality is called an industrial design registry. “8

The large volume of design work in an industrial sector that is oriented to production processes, is not classified as R & D. However, some elements of the design work, such as plans and drawings to define processes, technical specifications and operating characteristics necessary for the conception, development and manufacture of new products and processes, must be included as R & D.

Evaluation: It is the process of conceptualization or evaluation of a program, a project, a document, an information (among others), which necessarily implies the review by a scientific / academic / expert pair who as an evaluator must present a written concept of the evaluation – according to previously defined criteria – a concept that should be clearly supported.

Impact Evaluation: “Impact evaluation is a type of summative evaluation” 9. The World Bank 10 defines impact assessment as the measurement of changes in the well-being of individuals that can be attributed to a specific program or policy. Its general purpose is to determine the effectiveness of policies, programs or projects executed. The impact evaluation can be used to determine to what extent the planned results were produced or achieved, as well as to improve other projects or programs in execution or future (Brousseau and Montalvn, 2002) “11.

Layout Schemes of Integrated Circuits:

a) Integrated circuit: A product, in its final or intermediate form, whose elements, of which at least one is an active element and any or all of the interconnections, form an integral part of the body or surface of a piece of material, and that is intended to perform an electronic function;

b) Layout diagram: The three-dimensional arrangement, expressed in any form, of the elements, at least one of them being active, and interconnections of an integrated circuit, as well as that three-dimensional arrangement prepared for an integrated circuit destined to be manufactured.12

Project Risk Management13: Project risk management includes the processes to carry out the identification, analysis, assessment, response and control of the associated risks.

Guide14: A recommendation or official advice that indicates policies, standards or procedures about how something should be done.

Indicator: i) It is an instrument to measure the achievement of the objectives of the programs and a reference for monitoring progress and for evaluating the results achieved. ii) Tools to clarify and define, more precisely, objectives and impacts (…) are verifiable measures of change or result (…) designed to have a standard against which to evaluate, estimate or demonstrate progress ( …) with respect to established goals, facilitate the distribution of inputs, producing (…) products and reaching objectives15 “.

Executing Entity: Any income taxpayer that makes a capital or own resources placement that is recorded as a counterpart for the execution of a project in CTeI.

Administrative staff16: This category includes leaders, managers, administrators or managers who carry out administrative, economic and / or project management activities, as well as qualified and unskilled personnel for office support, maintenance, surveillance and secretariat, among others and that participates as support in the execution of the projects of CTeI. The fees of these personnel must be recorded in the project administration expense item.

Patent: “A patent is an exclusive right that is granted over an invention. That is, a patent is an exclusive right that is granted over a product or a process that, in general, offers a new way of doing something or a new technical solution to a problem. To obtain a patent, you must submit an application in which technical information about the invention is publicly disclosed. “17

Patent of invention: A patent of invention is the protection given to every new product or procedure, in all fields of technology, which offers a new way of doing something, or a new technical solution to a problem. The invention patent must be new (novelty), have an inventive level and be susceptible of industrial application.

Utility Model Patent: A utility model is considered as any new form, configuration or arrangement of elements, of any device, tool, instrument, mechanism or other object or part of it, that allows a better or different operation, use or manufacture of the object that incorporates it or that provides it with some utility, advantage or technical effect that it did not have before.18

Pilot plant19: “The Pilot Plant is defined as the process consisting of specific assembled parts that operate as a harmonious whole with the purpose of reproducing, at a scale, production processes.

It facilitates the subsequent operation and application at industrial level or in a certain work area; It also serves to compare theory (models) with practice and experimentation in various areas of knowledge. Its purpose is:

Predict the behavior of a plant at an industrial level, operating the pilot plant at conditions similar to those expected. In this case, the data obtained will be the basis for the design of the industrial plant.

Study the behavior of industrial plants already built, where the pilot plant is a replica and will be subject to the operating conditions foreseen for the industrial plant. In this case, the pilot plant is called a model and its main function is to show the effects of changes in operating conditions more quickly and economically than if they were carried out in the original plant. ”

The construction and use of a pilot plant are part of the R & D, as long as the main objective is to acquire experience and obtain technical or other data that can be used in:

– The evaluation of hypothesis.

– The development of new product formulas.

– The establishment of new finished product specifications.

– The design of special equipment and structures necessary for a new process.

– The drafting of operating instructions or manuals about the process.

– Standardization of batches of testing and development of production processes.

Once the experimental phase is completed, the pilot plant functions as a normal unit of commercial production. As of that moment, its activity can not be considered to be of R & D or technological development, even if the plant continues to be called a pilot plant. Since the fundamental objective of a pilot plant is not of a commercial nature, in principle it is irrelevant that part or all of its production may end up being sold20.

Prototypes21: A method to obtain an early feedback regarding the requirements, providing a functional operating model before actually building it.

Industrial prototype: Original built model that has all the technical and operational characteristics of the new product.

Once all the necessary modifications have been made to the prototype (s) and all the relevant tests have been carried out satisfactorily, the R & D phase is considered to be completed. The construction of several copies of a prototype to meet commercial, military or medical needs, once the original prototype has been successfully tested, does not constitute part of this phase, even though this activity is carried out by the expert staff in I + D22.

Project: “Project is a temporary effort that is carried out to create a product, service or unique result.” 23

CTeI Project: It is a coherent and comprehensive set of science, technology and innovation activities, which seek to achieve an ultimate goal through specific objectives, using a coordinated and interrelated methodology defined in a period of time, which can be supported in key elements such as: tools, human resources, support of guidelines and guidelines of senior management, essential technological or physical resources, in addition to previously estimated financial resources.

A CTeI project seeks to generate new knowledge, generate new products, services, organizational models, develop prototypes and / or pilot plants, develop experiments among others.

Responsible for the project before the CNBT, all the entities participating in the project will be responsible for the execution of the project and for the use of the benefit granted, according to their role and contributions. However, the entity responsible for coordinating the presentation of the project and the annual execution reports, will be the entity that provides the greatest resource to the project as an investor in the case of deductions, and in the case of donations, it will be the entity grantee

Risk (24): An uncertain event or condition that, if it occurs, has a positive or negative effect on one or more of the project’s objectives.

Role (25): A defined function to be performed by a member of the project team.

Transfer of knowledge and technology: The Transfer of Knowledge and Technology (TCT) defined from the perspective of the Innovation Systems, comprises a set of actions at different levels carried out by different institutions in an individual and aggregated way for the development, use, use, modification and diffusion of new technologies and innovations, and that constitutes the framework in which governments apply policies to contribute to innovation processes. (26)

The TCT requires a system of interconnected public and private institutions to create, store and transfer information, knowledge, skills and competencies. Usually the transfer is made with Intellectual Property assets through the following processes27:

  1. Sale of intellectual property rights.
  2. Licensing of intellectual property assets.
  3. Joint ventures or collaboration agreements.
  4. Generation of new technology-based companies (spin-off and start-up).

2. Typology of CTeI projects.

The definition of Science, Technology and Innovation projects is very broad and also involves efforts made by companies and the academic sector to generate new knowledge and materialize it in products and / or services, organizational models and processes that allow it to be more competitive and generate a social and economic impact.

In order to establish which projects can access the tax benefits, the National Council of Tax Benefits (CNBT) has established the conditions and characteristics of the projects that respond to the nature of the instrument and are aimed at generating value in the companies and the society.

For the Colombian case, scientific research projects, technological development and innovation are considered CII projects and are conceived as a systematic process that starts with the understanding of the foundations of observable phenomena and facts (basic research), ending with the introduction of implementation of solutions to problems faced daily by different sectors of society, which translates into the improvement of the country’s social and economic indicators.

CTeI projects are classified into three types: i. Scientific research projects, ii. Technological development projects and iii. Innovation projects.

2.1. Scientific Research Projects

Scientific research includes “creative work carried out systematically to increase the volume of knowledge, including knowledge of man, culture and society, and the use of that knowledge to create new applications.” (OECD, 2002) 28: The term Scientific research encompasses three modalities: basic research, applied research and experimental development, which can be defined according to the OECD (2002) as shown below:

Basic research “consists of experimental or theoretical works that are undertaken mainly to obtain new knowledge about the foundations of observable phenomena and facts, without thinking about giving them any application or specific use” .29 Regardless of the area of knowledge.

Applied research “also consists of original work carried out to acquire new knowledge; however, it is fundamentally directed towards a specific practical objective “30, regardless of the area of knowledge. Applied research is undertaken to determine the possible uses of the results of basic research, or to determine new methods or ways to achieve specific predetermined objectives.31

Experimental development “consists of systematic works based on existing knowledge obtained by research or practical experience, which are directed to the manufacture of new materials, products or devices, to establish new procedures, systems or services or to considerably improve those that already exist “ 32

The main objective of scientific research projects is the generation of new knowledge, with the aim of acquiring a deep understanding of the phenomena under study and the possible applications that may be made in the future. Table 2.1 shows the main objectives of the types of scientific research based on what is defined in the Frascati Manual.

Main objectives of the scientific research projects based on the Frascati manual:

Basic Research: Its main purpose is the generation of knowledge with two purposes: the first is to expand the volume of existing knowledge about a phenomenon and / or observable facts, the second has the objective of increasing the volume of knowledge available on a problem in order to to promote understanding for the future to develop a solution or application.

Applied research: Its main objective is to acquire new knowledge oriented towards a specific practical objective. To achieve this, all existing and available knowledge must be considered to solve specific problems.

Experimental Development: Its main objective is a deep understanding of the phenomena and factors that affect the materialization of an idea. It differs from applied research because in this type of project, there is a theoretical solution to a problem but it still does not meet the necessary conditions for the development of a functional prototype.

2.1.1. Projects that qualify as scientific research.

Projects that qualify as scientific research as defined by the National Council for Tax Benefits based on international manuals, could be summarized in table 2.2., Which contains illustrative and non-exhaustive examples to guide evaluators and proponents to identify in what type Your project can be located.

2.1.2. Projects that do not qualify as Scientific Research.

Projects that do not qualify as scientific research are those that by their scope or form of execution do not conform to what is defined by the National Council of Tax Benefits based on international manuals. Below is an enunciative list of these type of projects:

1. Projects that by their scope, structure and results may be considered Technological Development or Innovation.

2. Projects whose main objective is:

A) Teaching and training of personnel.

B) Development of undergraduate, Master and Doctorate theses.

C) Scientific, technological and technical information services.

D) Acquisition, collection and processing of data.

E) Tests and standardization of laboratory tests.

F) Accreditation of laboratories and bioterios.

G) Specialized technological and technical services.

H) Specialized consultancies

I) Administrative and legal activities aimed at obtaining property products

intellectual.

J) Pre-feasibility and / or feasibility studies.

K) Indirect management and support activities that do not constitute R & D in themselves.

L) Purchase, expansion, maintenance or update of infrastructure, equipment and machinery or computer programs.

M) Routine software use and maintenance activities.

N) Development of information systems that use known methods and tools

existing IT

O) The conversion or translation of computer languages.

P) The addition of user functions to those of computer applications.

Q) The debugging of computer systems.

R) The adaptation of existing software that does not imply new developments.

S) Strengthening of institutional capacities.

T) Activities that are of a routine nature and that do not imply scientific or technical advances or

do not solve technological uncertainties.

U) The creation of research centers, technological development centers, incubator of

companies, technological parks laboratories, among others.

3. Those developed in Free Zones based on the simple fulfillment of the Master Plan of

General Development of the Free Zone.

4. Those that are developed based on simple compliance with the regulations in force and / or obtaining certifications.

2.1.3. Content requested for the evaluation of a scientific research project.

In order to carry out the proposal evaluation process, the Technical Secretariat of the National Council of Tax Benefits has defined a series of contents requested in the online form for the registration of projects. Below is each of these contents with their respective description to guide proponents and / or evaluators in the process of qualifying the proposals as CTeI projects.

Title of Project

The title is the first reference of the project, it must describe the subject and the work to be done, for this it is important to take into account the content of the proposal and the purpose for which the research work is carried out. It is recommended to use a maximum of 250 characters for the title.

Amount requested for tax benefits for investment

The executing agency of the project must register in the online form what amount they request for the tax benefit during the duration of the project.

If there are more entities in the development of the project, this amount corresponds to the totality of the resources contributed by the participating entities and must coincide with the total value of the project without including the amounts financed with public resources.

The tax benefit applies only to the resources contributed by the income taxpayers that participate in the project and that are invested in the current and future fiscal period.

Type of Project

The type of project of a scientific research nature that is presented must be classified according to these options:

 Basic research

 Applied research 

 Experimental development

Justification of the nature of the project

Arguing the reasons why they consider that the project conforms to the type of scientific research, for this they may take into account the guidelines of the National Council of Tax Benefits consigned in this document and the own analysis that the proposer made at the time of formulating the proposal taking into account criteria such as the scope and purpose of the project. It is recommended to make a concise justification, which does not exceed 500 words and which answers the question What characteristics does the present project have that can be classified as a scientific research proposal?

Executive Summary

Summarize in a maximum of 500 words the necessary information to explain what the problem or need consists of, how you think it will solve it, what are the reasons that justify its execution and the tools that will be used in the development of the project.

Knowledge that will generate the research project (Identification and description)

Mention the new ideas or concepts that are important for scientific progress in the subject that contribute to achieving the proposed objectives. It is recommended to describe the relevance and contribution of the proposed project to the subject under investigation and explain how it will contribute to the generation of new scientific – technological knowledge or the advancement of the state of the art.

Statement of the problem or need

The approach of the problem makes it possible to identify the need to carry out the study and must be formulated in a clear and concrete manner, allowing the identification of the question or hypothesis to be answered, whose solution or understanding will contribute to the advancement of science and the generation of new knowledge.

The definition of the problem is one of the most complicated phases when formulating a project of any kind, since it must define what the problem consists of in a broad way, delimit it, and analyze if it is worthwhile to carry out a project to solve it. For scientific research projects it should be evident that there is a gap in the knowledge of a topic or for the materialization of a solution for the case of experimental development.

For this stage it is necessary to review the background and importance of the subject to be investigated, the previous studies carried out at national and international level and the way in which the development of the present investigation will contribute a new knowledge or allow the materialization of the knowledge in a good or service to future that satisfies a need.

State of the Art

The purpose of the elaboration of the state of the art is to give theoretical support to the problem posed and to the research that seeks to be carried out, and its objective is to know in depth the topic to be investigated and to identify the main advances obtained to date in this area of knowledge for guide research to generate new knowledge.

A state of the art must contain among other elements:

1. Analysis of the available scientific information on the subject, in order to corroborate that there is in fact a gap in knowledge. For this purpose, systematic searches of the scientific literature should be carried out to demonstrate the advance of scientific knowledge in this field. Remember that a state of the art must include the most recognized authors in the subject and an analysis of the works published in the last five years, as well as describe the main components and elements of the topic to be investigated.

2. The way in which the subject has been addressed in previous research, in this case, the results and methods used in the research that most closely approach the topic under study must be documented in order to guide the research to new ways of approaching the subject. problem or the identified need.

3. Know the perspectives or approaches of previous research on the related subject, so that new perspectives can be considered to analyze it, for example when studying the topic of traffic accidents in a region of Colombia, in the state of the art it is evident that the previous investigations focused on analyzing only the incidence of the road infrastructure and the safety of the vehicles that travel the most in this zone in the accident rate, for which a research that analyzes whether cultural and social factors affect said rate of accidents would generate new knowledge.

4. An analysis of similar cases of research at the regional, national or international level, in order to avoid “inventing the wheel” and take advantage of the results of previous research to generate new knowledge.

In case the project does not have direct antecedents or with a low number of publications, this situation should be evidenced by an analysis of the bibliography in recognized scientific sources.

In the case of projects with previous phases developed by the entity, the results achieved in the phases developed must be related.

For this item, it is recommended to take into account the analysis of technological surveillance, consult scientific databases and patents, relate bibliographic review (retaining the structure of formats such as the APA), and consult Scienti to verify the state of the national technique.

Remember to respect the intellectual property rights of article authors by citing them properly and including such references in the bibliography section.

Objectives of the project

The objectives define what is intended to achieve with the development of the project and become a guide during its execution as they define the scope of the research. When formulating an objective, it is necessary to verify that it is achievable and drafted clearly, in such a way that ambiguities or deviations are avoided throughout the development of the project. Below are some recommendations for its formulation:

The general objective of the project is one and you must establish that you intend to achieve the research, for that you must answer what and what you want to do the project for. It must be shown in a general way what will be the result of the research, the methods to be used and the challenge to be solved. It is recommended to write with a verb in infinite that translate action for example establish, implant, synthesize, analyze, develop among others.

The specific objectives define the aspects, phases and / or main stages that are needed to reach the general objective, they must be coherent with each other and show what the results and methods are for each phase of the project. It is recommended to establish a maximum of 5 objectives and write starting with a verb in infinitive.

Main errors in the formulation of objectives:

1. Confuse objectives with activities, processes or procedures.

2. Repeat the general objective within the specific objectives, remember that the general objective is the purpose of the project and the specific objectives detail the

main phases to achieve it.

3. Write objectives that are not consistent with the title and the problem

raised, remember that the projects have a common thread that begins with the

Title.

4. Write objectives ambiguously so that it is not possible to identify

who is looking for the project and what the results will be.

5. Explain the objectives, given that in this field only those are defined, the objectives are justified with the problem and state of the art and are explained in the methodology.

Proposed Methodology

The methodology defines the way forward to achieve the proposed objectives, and must identify and describe the use of qualitative and quantitative methods, procedures, analytical techniques that will be used to achieve each of the specific objectives.

It is recommended to write the methodology by specific objective and define for each of them, the procedure, technique or tool to be used, for example observations, surveys, interviews, experimental designs, simulations, validations, tests, tests and others, the variables to analyze when applicable and the information or data that you aspire to obtain and the results.

Main errors in the formulation of the methodology:

1. Write the methodology as a list of activities, this is done in the project schedule

2. Define the methodology with little detail, given that without sufficient information an evaluator of the proposal could consider that the objectives are not attainable.

Project Risks

Risks are an event or condition of uncertainty that, when materialized, can have a positive or negative effect on the scope of one or more project objectives (PMI, 2013).

In this item, it is requested to record the main risks that the entities have identified that could impact the execution of the project and the activities or control points for their mitigation. This information is necessary to follow the project.

In the case of the evaluation of the proposals, the evaluators will verify that the identified risks allow to reduce the uncertainty of reaching the proposed objectives.

It is suggested to write the risks based on the following structure: “As a result of (enter the cause), there is a possibility that (possible future event) causing (enter the effect)” for example as a result of inadequate handling of samples, there is the possibility that the results of the laboratory tests are not as expected, causing the specific objective not to be reached 1. For this risk, the entity defines safety and sample management protocols and includes tools that allow researchers to constantly monitor the conditions environmental aspects of laboratory tests.

Trajectory and capacity of the working group or institutions participating in the project

Describe the experience and trajectory that the executing and co-executing entities and the actor recognized by Colciencias have in the subject of the proposed project, it is suggested to include previous research, products obtained, publications, presentations, technical documents, among others.

In case an entity considers that the information included in the Scien-ti platform is sufficient to evaluate the trajectory and capacity, include in this item the information about the group to be validated in the evaluation process.

Distribution of project responsibilities:

Clearly describe the activities and deliverables that will be developed in the execution of the

a) The executing agency

b) Co-executing entities

c) The actor recognized by Colciencias

d) The entities and / or persons that will carry out specialized consulting activities. 

e) The entities that will perform technological services within the framework of the project.

Bibliography

Relate the sources of scientific and / or technological information relevant, current and / or updated that were consulted and / or cited in the text of the project. It is recommended to use sources recognized by the national or international scientific and technological community and the APA, ISO or MLA formats for citations. The proponent of the project is responsible for making the respective citation of the documents consulted.

Environmental Impact in the execution of the Project

Identify the effects of the development of the research project, whether positive or negative. In the event that the project identifies a negative environmental impact, it must identify if it is necessary to obtain the permits and environmental authorizations issued by the competent authorities that enable the development of the project. It is recommended to establish the pertinent actions to mitigate the negative environmental impacts identified.

Remember that with the joint signature of the letter of presentation, endorsement and acceptance of commitments, the project entities certify that “The present project was formulated taking into account the environmental norms, norms of health research or applied, in the case of genetically modified organisms or access to biological and genetic resources, or in case of using live resources, agents or biological samples, personal data, information from previous research carried out with living beings or that have no impact on life. And they have the respective supports (ethics committee, environmental licenses among others), in case COLCIENCIAS requires them “.

If, to the consideration of an evaluator, a project that requires a special permit for its execution, the supports may be requested to the proponents in the feedback stages and in case of not sending it, the National Council of Tax Benefits may reject its proposal due to non-compliance the requirements established by law.

Aspects of Intellectual Property

The entities participating in the project must define the ownership of the intellectual property rights derived from the results, taking into account the roles of the parties involved and their functions in the project. For more information, consult the Intellectual Property Guide adopted by the CNBT available on the Colciencias website. If there are no results that can be protected by intellectual property or that other protection mechanisms are defined, this should be explicitly stated.

Technical results by specific objective.

Relate for each specific objective the results that show its scope.

In the event that I consider that there are other results than those registered in the “results” field, they may be included in this space and identify the characteristics of new knowledge generated, means of verification and indicators thereof.

 

Schedule

To relate the main activities required for the execution of the project based on what is defined in the methodology and to limit them in a period of time, in such a way that it allows to observe all the execution of the project and to know the progress status. It is advisable to take into account possible contingencies and / or delays that may arise during the execution of the project when defining its duration.

Remember that for the development of this project, you may apply to the CNBT for an extension for the execution of the project only when it is not possible to obtain the technical results in the time initially stipulated, this extension may not exceed one year.

Results

Define the measurable and quantifiable products that will be reached with the development of the project. It is necessary to establish at least one result for each specific objective and indicate the characteristics of new knowledge generated, means of verification and indicators.

Remember that these results must be fully achieved within the framework of the project development and must be consistent with the methodology and demonstrate compliance with the project’s objectives.

Example of indicators: number of indexed publications, tests carried out, presentations, laboratory tests developed, experiments performed, etc. (during the execution of the project). A guide to the possible results can be found in section 5 of this document.

Expected Impacts

Relate the expected medium and long-term effects with the development of the project as a result of the knowledge acquired and generated in the research.

It is important to identify for each impact, the qualitative and quantitative indicators that can be verified, their description and the year of measurement. An example of indicators could be: number of new publications made by participating entities, number of prototypes developed, number of projects developed based on the knowledge generated, among others.

Budget

The budget of the project gives financial backing to the proposal and becomes one of the restrictions that limit the scope of the project. It is for this reason that it must be directly related to the activities defined in the methodology and the resources required to achieve the objectives.

In this item, the entity must record the values of the investment in the project within the framework of the items approved by the National Council for Tax Benefits (CNBT) for tax purposes. These can be consulted in number 3. It is important to register the

Provider when a purchase is made to other entities and the justification of why this item is necessary in the project and its relation with the proposed methodology and activities. Likewise, it is recommended to break down the items in detail and not to group investments in large items (for example: acquisition of machinery necessary for the development of the project).

To plan these items, it is necessary to make an estimate of costs taking into account factors such as inflation and the projection of the value of the dollar, so that the company can access the tax benefit in an appropriate manner. Remember that you will not be able to increase the value of the budget registered for tax purposes, so that investments with amounts higher than those approved by the CNBT will not be able to access the tax benefit. Entities may only make a quota transfer for tax purposes throughout the life cycle of the project.

2.1.4. Qualification criteria for a scientific research project. 

Quality of the project, 

(viability(33) of the project): (74%)

to)

b) Formulation of the proposal: (1%)

i) It will be verified that the registered project has been formulated taking into account the project typology document approved by the CNBT.

Quality of the proposed concepts: (5%) will be considered

i) The quality of the proposed research or development actions, as the case may be and

proposed methods for the execution and monitoring of the project, which guarantee the approach of

the proposed objectives.

ii) The quality of the project’s background, that is, whether the project is adequate and updated.

Information provided on:

  • The theme of the project.
  • The state of the art in the subject.
  • The approach of the problem.
  • The bibliographic review.

 Aspects related to technological surveillance or other pertinent documentation

that leads to identify the added value provided by the development of the project at the local, sectoral, regional, national or international level.

Quality and efficiency of project planning. (68%) 

It will be verified

  1. The clear and coherent definition of the specific objectives set to achieve the general objective.
  2. The coherence and relevance of the methodology and the activities to be developed in order to achieve the objectives and results proposed.
  3. The technical expertise of the participants that make up the work team, necessary to perform the tasks assigned within the project. The knowledge and verifiable technical trajectory related to the theme of the submitted proposal must be assessed.
  4. The coherence of the time spent by the work team in the activities to be developed.
  5. The consideration of technological competitiveness for technological development or 
  6. innovation projects, that is, the advantages for the country, the risk of obsolescence and the possibility of generating patents
  7. The coherence between the proposal and the administrative and technical management capacity of the group or recognized center that co-executes or supervises the project to qualify.
  8. The clarity and coherence of the distribution of budgeted resources in the project. He
  9. It will verify that the budgeted items are necessary to achieve the objectives, are clearly defined, justified and conform to the project typology document.

Potential impact of the project through the development, dissemination and use of project results. (20%) 

It will be verified:

 III.

Relevance of the project. (6%) 

It will be verified:

  1. The contribution to the strengthening of the country’s research and development. 
  2. The contribution with scientific training, knowledge transfer or new technologies.
  3. The clear, coherent definition of the expected results for each of the specific objectives.
  4. The contribution and implementation of the added value provided by the results of the project.
  5. For research projects: identify contributions of new knowledge.
  6. The identification of the results with verifiable quantitative and qualitative indicators.
  7. The strengths of intellectual property.
  8. The validity and relevance of the means and type of proposed disclosure.

2.2. Technological Development Projects

Technological development is understood as: “Application of the results of research, or any other type of scientific knowledge, for the manufacture of new materials, products, for the design of new processes, production systems or services, as well as the substantial technological improvement of pre-existing materials, products, processes or systems. This activity will include the realization of the results of the research in a plan, scheme or design, as well as the creation of non-marketable prototypes and the initial demonstration projects or pilot projects, provided that they are not converted or used in industrial applications or for commercial exploitation “.34

The main objective of these projects is the materialization of the knowledge available or obtained by the entities participating in the project, in prototypes, pilot plants, models to validate their usefulness in satisfying a need whether internal, external or from the market.

Technological development is considered as the first phase of innovation, and include in its scope the manufacture of test batches at pilot scale for the case of new products or the development of pilot plants for the validation of new production processes.

Experimental development projects differ from technological development because in this type of research, there is a theoretical solution to a problem but it still does not meet the necessary conditions for the development of a prototype. Its objective is a deep understanding of the phenomena and factors that affect the materialization of an idea and not in the development of prototypes.

2.2.1. Projects that qualify as Technological Development.

The projects that qualify as technological development as defined by the National Council of Tax Benefits based on international manuals, are summarized in the following table, which contains illustrative and non-exhaustive examples to guide evaluators and proponents to identify in what type tour project can be located.

Features

Technological development projects validate solutions at the prototype and pilot level, before scaling up at an industrial level, its objective is to reduce the uncertainty generated by the theoretical solutions proposed.

Possible Results 

Prototypes, pilot plants, models

Design, optimization and / or standardization of pilot-level processes.

Validation of design and its impact on improving the quality of goods or services.

Development of information technologies in relation to operating systems, programming languages, data management, programs of communications and tools for software development.

The development of software that produces advances in the generic approaches for the capture, transmission, storage, recovery, treatment or presentation of information.

R & D in software tools or technologies in specialized areas of computer science (image processing, presentation of data recognition characters, artificial and others).

Geographic, intelligence interactives, prototypes and artifacts for science centers.

Examples

  • Design of a prototype of bumper and directions in low range cars from thermoplastic polyurethanes, with greater resistance to friction and tenacity, for automobiles.
  • Design of a pilot plant for the analysis of the efficiency of the reading system by means of bluetooth, for the traceability of products.
  • Application of algorithms based on neural networks for the development of pilot software for traffic lights in cities.
  • Pilot plant for potassium nitrate for the manufacture of fertilizers in citrus fruit plantations
  • Prototypes for the development of intelligent textiles from nanotechnology processes.
  • Prototypes for the development of reverse engineering for the production of mechanical parts in the automotive sector.
  • Development and validation of robot prototypes for automation processes that improve the productivity and / or efficiency of the plant.

2.2.2. Projects that do not qualify as Technological Development.

Projects that do not qualify as Technological Development are considered to be those that by their scope or form of execution do not conform to what is defined by the National Council of Tax Benefits based on international manuals. Below is an enunciative list of this type of projects:

1. Projects that by their scope, structure and results can be considered as scientific research or Innovation.

2. Projects that consist essentially of technological services and / or specialized consultancies.

3. Projects whose main objective is:

A) Regular or periodic modifications made to products, production lines, manufacturing processes, existing services and other operations in progress, even when said modifications may represent improvements to them.

B) Scaling at an industrial level35 or commercialization of the results obtained or developed at the pilot plant level.

C) Routine efforts36 to improve products, processes or services.

D) Routine adjustments made by the company due to its normal operation or leveling with

with respect to competitors that does not imply a development by the executing company.

E) Periodic changes, seasonality or seasonal changes (eg fashion design), that do not imply

changes in the functionality of the products.

F) Design changes that do not modify the functionality of the product or service.

G) Aesthetic modifications of existing products to differentiate them from similar ones.

H) Marketing of products and services of other companies, including parent companies.

I) Consulting

J) The replacement, purchase, expansion or update of infrastructure, machines, equipment or

Software.

K) Strengthening institutional capacities

L) Pre-feasibility studies (37), feasibility (38).

M) Hiring technological services and / or specialized technicians.

N) Administrative and legal activities aimed at obtaining property products

intellectual

O) Indirect management and support activities that do not constitute R & D in themselves.

P) Computer activities that are routine in nature and do not involve advances

scientists, technicians, who do not resolve technological uncertainties or who do not demonstrate their CTeI component.

Q) Commercial application software and development of information systems that use methods

known and existing computer tools.

R) The maintenance of existing computer systems.

S) The conversion or translation of computer languages.

T) The debugging of computer systems.

U) The adaptation of existing software.

V) The preparation of documentation for the user.

W) Teaching and training of personnel, development of undergraduate thesis, Masters and Doctorate.

X) Scientific, technological and technical information services.

Y) Acquisition, collection and processing of data.

Z) Tests and standardization of laboratory tests.

3. Those developed in Free Trade Zones according to the simple fulfillment of the General Development Master Plan of the Free Trade Zone.

4. Those developed based on simple compliance with current regulations and / or obtaining certifications.

2.2.3. Content requested for the evaluation of a Technological Development project.

In order to carry out the proposal evaluation process, the technical secretariat of the National Tax Benefits Council has defined a series of contents requested in the online form for the registration of projects. Below is each of these contents with their respective description to guide proponents and / or evaluators in the process of qualifying the proposals as CTeI projects.

Information requested by Colciencias

Title of the project

The title is the first reference of the project, it must describe the subject and the work to be done, for this it is important to take into account the content of the proposal and the purpose for which the research work is carried out. It is recommended to use a maximum of 250 characters for the title.

Amount requested for tax benefits for investment

The executing agency of the project must register in the online form what amount they request for the tax benefit during the duration of the project.

If there are more entities in the development of the project, this amount corresponds to the totality of the resources contributed by the participating entities and must coincide with the total value of the project without including the amounts financed with public resources.

The tax benefit applies only to the resources contributed by the income taxpayers that participate in the project and that are invested in the current and future fiscal period.

Project Type

The type of project must be classified, for this case it is Technological Development.

Justification of the nature of the project

Argument the reasons why they consider that the project conforms to the type of Technological Development. For this purpose, they may take into account the guidelines of the National Council of Tax Benefits consigned in this document and the own analysis that the proposer made at the time of formulating the proposal, taking into account criteria such as the scope and purpose of the project. It is recommended to make a concise justification, that does not exceed 500 words and that answers the question: What characteristics does this project have that can be classified as a Technological Development proposal?

Technological development of the proposal (identification and description)

Mention the new ideas or concepts that are important for the scientific and technological advance in the subject that contribute to achieving the proposed objectives. It is recommended to describe the relevance and contribution of the proposed project to the subject under investigation and explain how they will contribute to the materialization of an idea in a prototype, pilot plant, model among others.

Pre-evaluation of the market for technological development.

Mention what are the needs and opportunities of the market identified for this project. For this purpose, it will have to consult or identify needs with customers, analyze competitors and the market and, as far as possible, characterize the potential market for new products and, for processes and / or organizational models, the needs of the company in comparison with the available solutions.

Statement of the problem or need

The approach of the problem allows to identify the need and / or opportunity to carry out the study and must be formulated in a clear and concrete way, allowing identifying the need or opportunity that one wants to replace with the development of the project and the scientific / technological uncertainty whose solution or understanding it will contribute with the materialization of available knowledge in a tangible good or service at the prototype or pilot level.

The definition of the problem is one of the most complicated phases when formulating a project of any kind, since it must define what the problem consists of in a broad way, delimit it, and analyze if it is worthwhile to carry out a project to solve it. For technological development projects, it should be evident that there is a challenge in the materialization of a theoretical solution, that merits a stage of development and validation of the same before implementing it or launching it into the market.

For this stage it is necessary to review the background and importance of the subject to be investigated, the previous studies carried out at national and international level and the way in which the development of the present investigation will allow the materialization of the knowledge in a good or service that satisfies a need in the medium term.

State of the Art

The purpose of the elaboration of the state of the art is to give theoretical support to the problem posed and to the project that seeks to be carried out, and aims to know in depth the topic to be investigated and to identify the main advances obtained to date in this area of knowledge for guide the project to the development of a prototype or pilot plant that will allow an improvement of existing products and solutions.

A state of the art must contain among other elements:

  1. Analysis of the available scientific information on the subject, in order to corroborate that there is a real challenge in the materialization of these solutions. For this purpose, systematic searches of the scientific literature should be carried out to demonstrate the advance of scientific knowledge in this field. Remember that a state of the art must include the most recognized authors in the subject and an analysis of the works published in the last five years, as well as describe the main components and elements of the topic to be investigated.
  2. The way in which the subject has been addressed in previous research and / or projects. In this case, the results and methods used in the investigations that are closest to the topic under study and / or to the possible prototypes or pilot plants developed must be documented, in such a way that it guides the project to new ways of approaching the problem or the identified need.
  3. The perspectives or approaches of previously developed projects on the related subject, in such a way that new perspectives can be considered to analyze it. For example, a company proposes a project for the design of a prototype of an aquatic robot, in the state of the art they review the possible materials with which they can comply with the designs and identified that there is a type of alloy that is malleable and resistant to high hydrostatic pressures but that has never been used to build a robot, so they decide to include it for the development of the project.
  4. An analysis of similar cases of research at the regional, national or international level, in order to avoid “inventing the wheel” and take advantage of the results of previous research to generate new functional prototypes, improvements in pilot plants, new models, others.
  5. In case the project does not have a direct background or with a low number of publications, this situation should be evidenced by an analysis of the bibliography in recognized scientific sources.
  6. In the case of projects with previous phases developed by the entity, the results achieved in the phases developed must be related.
  7. For this item, it is recommended to take into account the analysis of technological surveillance, consult scientific databases and patents, relate bibliographic review (retaining the structure of formats such as the APA), and consult Scienti to verify the state of the national technique.
  8. Remember to respect the intellectual property rights of article authors by citing them properly and including such references in the bibliography section.

Objectives of the project

The objectives define what is intended to achieve with the development of the project and become a guide during its execution as they define the scope of the research. When formulating an objective, it is necessary to verify that it is achievable and drafted clearly, in such a way that ambiguities or deviations are avoided throughout the development of the project. Below are some recommendations for its formulation:

The general objective of the project is one and you must establish that you intend to achieve the research, for that you must answer what and what you want to do the project for. It must be shown in a general way what will be the result of the research, the methods to be used and the challenge to be solved. It is recommended to write with a verb in infinitive that translates action for example establish, implant, synthesize, analyze, develop among others.

The specific objectives define the aspects, phases and / or main stages that are needed to reach the general objective, they must be coherent with each other and show what the results and methods are for each phase of the project. It is recommended to establish a maximum of 5 objectives and write starting with a verb in infinitive.

Main errors in the formulation of objectives:

Confuse objectives with activities, processes or procedures.

Repeat the general objective within the specific objectives, remember that the general objective is the purpose of the project and the general objectives detail the main phases to achieve it.

Write objectives that are not consistent with the title and the problems raised, remember that the projects have a common thread that begins with the title.

Draft objectives in an ambiguous way so that it is not possible to identify what the project is looking for and what the results will be.

Explain the objectives, given that in this field only those are defined, the objectives are justified with the problem and state of the art and are explained in the methodology.

Proposed Methodology 

The methodology defines the way forward to achieve the proposed objectives, and must identify and describe the use of qualitative and quantitative methods, procedures, analytical techniques that will be used to achieve each of the specific objectives.

It is recommended to write the methodology by specific objective and define for each of them, the procedure, technique or tool to be used, for example simulations, validations, tests, tests, among others, the variables to be analyzed when applicable and the information or data that aspire to obtain and the results.

Main errors in the formulation of the methodology:

Write the methodology as a list of activities, this is done in the project schedule

Define the methodology with little detail, given that without sufficient information an evaluator of the proposal could consider that the objectives are not achievable.

Project Risks

Risks are an event or condition of uncertainty that, when materialized, can have a positive or negative effect on the scope of one or more project objectives (PMI, 2013).

In this item, it is requested to record the main risks that the entities have identified that could impact the execution of the project and the activities or control points for their mitigation. This information is necessary to follow the project.

In the case of the evaluation of the proposals, the evaluators will verify that the identified risks allow to reduce the uncertainty of reaching the proposed objectives.

It is suggested to write the risks based on the following structure: “As a result of (enter the cause), there is a possibility that (possible future event) causing (enter the effect)” for example as a result of an inadequate design of a functional prototype , there is the possibility that the prototype does not meet the identified needs, causing the specific objective not to be reached. 

1. For this risk, the entity defines a validation with design experts before making the prototype.

Trajectory and capacity of the working group or institutions participating in the project

Describe the experience and trajectory that the executing and co-executing entities and the actor recognized by Colciencias have in the theme of the proposed project. It is suggested to include previous research, products obtained, publications, presentations, technical documents, among others.

In case an entity considers that the information included in the Scien-ti platform is sufficient to evaluate the trajectory and capacity, include in this item the information about the group to be validated in the evaluation process.

Distribution of responsibilities

Clearly describe the activities and deliverables that will be developed in the execution of the project: 

  1. The executing entity. 
  2. Co-executing entities. 
  3. The actor recognized by Colciencias. 
  4. The entities and / or persons that will carry out specialized consulting activities. 
  5. The entities that will perform technological services within the framework of the project.

Bibliography

Relate the sources of scientific and / or technological information relevant, current and / or updated that were consulted and / or cited in the text of the project. It is recommended to use sources recognized by the national or international scientific and technological community and the APA, ISO or MLA formats for citations. The proponent of the project is responsible for making the respective citation of the documents consulted.

Environmental Impact in the execution of the Project

Identify the effects that the development of the research project has, whether positive or negative. In the event that the project identifies a negative environmental impact, it must identify if it is necessary to obtain the permits and environmental authorizations issued by the competent authorities that enable the development of the project. It is recommended to establish the pertinent actions to mitigate the negative environmental impacts identified.

Remember that with the joint signature of the letter of presentation, endorsement and acceptance of commitments, the project entities certify that “The present project was formulated taking into account the environmental norms, norms of health research or applied, in the case of genetically modified organisms or access to biological and genetic resources, or in case of using live resources, agents or biological samples, personal data, information from previous research carried out with living beings or that have no impact on life. And they have the respective supports (ethics committee, environmental licenses among others), in case COLCIENCIAS requires them “.

If, to the consideration of an evaluator, a project that requires a special permit for its execution, the supports may be requested to the proponents in the feedback stages and in case of not sending it, the National Council of Tax Benefits may reject its proposal for non-compliance the requirements established by law.

Aspects of Intellectual Property

The entities participating in the project must define the ownership of the intellectual property rights derived from the results, taking into account the roles of the parties involved and their functions in the project. For more information, consult the Intellectual Property Guide adopted by the CNBT available on the Colciencias website. If there are no results that can be protected by intellectual property or that other protection mechanisms are defined, this should be explicitly stated.

Technical results by specific objective.

Relate for each specific objective the results that show its scope. In the event that I consider that there are other results than those registered in the “results” field, they may be included in this space and identify the characteristics of new knowledge generated, means of verification and indicators thereof.

Schedule

To relate the main activities required for the execution of the project based on what is defined in the methodology and to limit them in a period of time, in such a way that it allows to observe all the execution of the project and to know the progress status. It is advisable to take into account possible contingencies and / or delays that may arise during the execution of the project when defining its duration.

Remember that for the development of this project, you may apply to the CNBT for an extension for the execution of the project only when it is not possible to obtain the technical results in the time initially stipulated, this extension may not exceed one year.

Results

Define the measurable and quantifiable products that will be reached with the development of the project, it is necessary to establish at least one result for each specific objective and indicate the characteristics of new knowledge generated, means of verification and indicators.

Remember that these results must be fully achieved within the framework of the project development and must be consistent with the methodology and demonstrate compliance with the project’s objectives.

Example of indicators: number of functional prototypes, tests performed, presentations, laboratory tests developed, pilot plants, experiments performed, etc. (during the execution of the project). A guide to the possible results can be found in section 5 of this document.

Expected Impacts

Relate the expected medium and long-term effects with the development of the project as a result of the knowledge acquired and generated in the research.

It is important to identify for each impact, the qualitative and quantitative indicators that can be verified, their description and the year of measurement. An example of indicators could be: number of new publications made by participating entities, number of prototypes developed, number of projects developed based on the knowledge generated, among others.

Personal

Register the necessary personnel for the execution of the project by participating entity. The scientific and support staff must be registered and clearly define the function in the project, role, specialty and function. To know the type of scientific and support staff consult section 4.2.

It is necessary to define a principal investigator in the project and identify which is the scientific staff of the proposal, since it will be the only one that will be able to access the benefit of Non-Constituent Income of Income and / or Occasional Gain.

Budget

The project budget gives financial support to the proposal and becomes one of the restrictions that limit the scope of the project, which is why it must be directly related to the activities defined in the methodology and the resources required to achieve the objectives. 

In this item, the entity must register the investment values in the project within the framework of the items approved by the National Council for Tax Benefits (CNBT) for tax purposes. These can be consulted in number 3. It is important to register the supplier when make purchase to other entities and the justification of why this item is necessary in the project and its relation with the methodology and activities proposed. Likewise, it is recommended to break down the items in detail and not to group investments in large items (for example: acquisition of machinery necessary for the development of the project).

To plan these items it is necessary to make an estimate of costs taking into account factors such as inflation and the projection of the value of the dollar so that the company can access the tax benefit in an appropriate manner. Remember that you will not be able to increase the value of the budget registered for tax purposes, so that investments with amounts higher than those approved by the CNBT will not be able to access the tax benefit. Additionally, entities may only make a quota transfer for tax purposes throughout the life cycle of the project.

2.2.4. Qualification criteria for a Technological Development project.

Relevance of the Project: (50%)

It will be evaluated that:

1. The proposal of technological development points to the materialization of available knowledge and responds to a real need of the market identified, quantified and characterized by the company.

2. The proposal is duly formulated and the proposed activities point to the realization of the available knowledge at the prototype or pilot level.

3. In the proposal, there is a clearly identified market with potential customers and requirements of the defined products or processes that will be developed and validated in the project.

4. The scientific staff has experience in the scope of application of the project and has been immersed in other processes of technological development previously executed. The knowledge and verifiable technical trajectory related to the theme of the submitted proposal must be assessed.

5. The company has the capacity of infrastructure and equipment necessary for the development of the project and to allocate the necessary resources for its successful execution.

6. The support staff defined in the proposal is sufficient to perform the tasks assigned within the project.

7. There is coherence between the time spent by the work team and the activities to be developed.

8. There is coherence between the proposal and the administrative and technical management capacity of the group, center, R & D & I unit recognized or the researcher who co-executes or supervises the project to be qualified.

9. The distribution of budgeted resources in the project is coherent and sufficient. It will be verified that the budgeted items are necessary for the achievement of the objectives, are clearly defined, justified in the proposal and conform to the project type document.

10. The Technological Development proposal has previous studies or theoretical background that provide support to the proposed solution and contains novel elements that have not been implemented or developed previously and that pose a challenge for the company.

Quality of the project: (30%) 

It will be verified:

  1. There is coherence between the description of the problem or need, the state of the art, the challenge or opportunity to be addressed and the objectives of the project.
  2. The results of the project point to the materialization of the results of previous research stages that lead to the development at the pilot or prototype level of new products, organizational models processes.
  3. The proposed methodology allows the obtaining of results, the scope of the general objective and responds to the nature of a technological development project.
  4. The project clearly evidences the difference between what exists in the company and the challenge and / or challenge that the company faces with the development of the proposal.
  5. The technological development contains theoretical foundations that give viability to the project and satisfy a quantified and identified need.
  6. Within the postulated project, there are activities that allow the appropriation of the knowledge generated by the company, the sector and / or country, or the patent application on the obtained development.

Impact of the project: (20%) 

It will be verified:

  1. There is a clearly identified proposed strategy within the company to capture the added value of the project and scale it up in future stages.
  2. The development of the project, will result in the materialization of knowledge in a prototype or pilot of a new or significantly improved product or service, or a new organizational model for the company, the country or internationally.
  3. The economic, social, technological, environmental and cultural impact of technological development has been identified and quantified and is considered significant compared to the identified problem situation.
  4. The contribution with the scientific training, knowledge transfer or new technologies that aim at the competitiveness of the companies and the productive sector.

 

NOTE: The minimum qualification for the approval of a project will be 80 points.

2.3. Innovation Projects

An innovation is the introduction to the use of a product (good or service), of a process, new or significantly improved, or the introduction of a new marketing or organization method applied to business practices, work organization or external relations “(39).

For there to be innovation, it is necessary, at least, that the product (good or service), the process, the marketing method (40) or the method of organization are new or significantly improved for the company.

“Innovative activities correspond to all scientific, technological, organizational, financial and commercial operations that effectively lead, or that aim to lead the introduction of innovations. Some of these activities are innovative in themselves, others are not new but are necessary for the introduction of innovations. Innovation activities also include R & D activities that are not directly linked to the introduction of a particular innovation “ (41).

Innovation should be considered as a continuous process, based on a methodology that generates knowledge, the use of new technologies or the generation of innovation opportunities. For purposes of the instrument of Tax Benefits for investment, the National Council of Tax Benefits in Science, Technology and Innovation has defined that the following may be considered as innovation projects:

Product Innovation 

“A product-service innovation is the introduction of a new or significantly improved good or service with respect to its characteristics or possible uses. This type of innovation includes significant improvements in technical specifications, components, materials, embedded software, ergonomics or other functional characteristics. “Significant improvements of existing products may be the result of changes in materials, components or other features that improve their performance43. Service innovations can include significant improvements in supply operations (for example, in terms of efficiency or speed), the addition of new functions or features to existing services, or the introduction of entirely new services44.

Innovation in Process 

“A process innovation is the introduction of a new or significantly improved production or distribution method. It includes significant improvements in techniques, equipment or software45. In services, process innovations include new or significantly improved methods for the creation and delivery of them. Innovation in the process includes innovations in the methods of distribution and production, in the former they are linked to the logistics of the company and include the equipment, the computer programs, the techniques for supplying inputs, the allocation of supplies within the company or the distribution of final products. Production methods include techniques, equipment and programs that can be used to produce goods or services.

Organizational Innovation 

“Organizational innovation is the introduction of a new method of organization applied to business practices, to the organization of work or to the external relations of the company46”. The differentiating characteristic of an organizational innovation, compared with other changes organizational, is the application of a new organizational method (to business practices, to the organization of work or external relations) that has not been used before in the company and that is the result of strategic decisions of the management (47). Within the organizational innovation is among others:

  • Innovations in the organization of the workplace (48): These innovations imply the introduction of new methods of attribution of responsibilities and decision-making power among employees for the division of labor, or of new structuring concepts.
  • Innovations in foreign relations (49): involve the introduction of new ways of organizing relationships with other companies, research organizations, clients, suppliers and public institutions.

The main objective of innovation projects is the introduction into the market of a product or service or the implementation of a new process on an industrial scale or an organizational method in all the areas involved.

Innovation in product: Its main purpose is the introduction of new products or services for the sector, the region or the country or significantly improved, that is to say that they modify some characteristic of the product in such a way that they have better performance.

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Process innovation: Its main objective is the introduction of new processes for the production of a product or provision of a new or significantly improved service, that is to say that they modify components of the process to improve the performance of the process in terms of cost reduction and increase Of capacity. The main difference between a process innovation and a product innovation is that the first is focused on improving the way the product is made while the second is focused on improving the characteristics of the product.

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Organizational innovation: Its main objective is to introduce new organizational models in the company, and is focused mainly on people and / or work organization, while process innovation refers more to the introduction or modification of the components of the process to improve its performance, efficiency, among others.

Table 2.6. Main objective of the innovation project types.

2.3.1. Projects that qualify as Innovation

Projects that qualify as innovation as defined by the National Tax Benefits Council based on international manuals, could be summarized in the following table, which contains illustrative and non-exhaustive examples to guide evaluators and proponents to identify which type can be located her project.

Typology

Product or service innovation features introduce new or significantly improved products or services for the sector.

Possible Results

  • Substitution of products or imports.
  • Development of friendly products with the environment.
  • Development of functionalities increase the aggregate of the product or service.
  • Entry to new markets.
  • Increase market share.
  • Improvement of quality of goods and services.

Examples

1. Introduction to the market of pest biocontrollers in crops.

2. Validation and introduction to the market of a bumper to from thermoplastics, production, marketing, manufacturing plant.

3. Implementation of a mobile application of an early warning system, based on data analysis with Big data technology, for inhabitants in populations at high risk of flooding or avalanche by increasing rivers.

Typology: Process innovation

Features

Implementation of new or significantly improved manufacturing processes or service provision.

Possible Results

  • Reduction of response times to the needs of customers.
  • Reduction of consumption of raw materials and energy.
  • Improvements in the flexibility of the production process or the provision of services.
  • Increases in production capacity or provision of services.
  • Reduction of labor costs. Reduction of product out of specifications.
  • Reduction of product design costs.
  • Reduction of operating costs for the provision of services.
  • Optimization of a process.
  • Significant improvement in the quality of service
  • Reduction of environmental impacts.
  • Reduction of response times to customer needs.

Examples

1. Implementation in the company of a product traceability system through bluetooth, to reduce the quantity of non-conformed products marketed and identify the critical points of Process Control.

2. Implementation of a telemedicine system in rural hospitals for the treatment of chronic diseases.

3. Improvement of Efficiency in electrical systems through the transfer and dissemination of new knowledge in management.

4. Implementation of a system for smart traffic lights in large cities.

Typology:  Organizational Innovation

Features

Implementation of new organizational models at work, mainly in the organization of the workplace, the external relations of the company or the application of new organizational methods.

Possible Results

  • Administrative transaction reduction.
  • Reduction of supplies and/or of costs
  • Significant improvement of working conditions.
  • Improvement in communications and interactions between the different business units.
  • Increase in the transfer of knowledge with other organizations.
  • Increased ability to adapt to changes in customer demand.
  • Increase in the efficiency or speed of the supply / distribution chain and / or shipment of goods and services.
  • Development of new methods of relationship with customers and / or suppliers
  • Development of new capabilities that have a different impact on the business model.

Examples

Auto parts supplier development program: Management model for competitiveness

Incorporation of new practices to the business model.

2.3.2. Projects that do not qualify as Innovation.

Projects that do not qualify as innovation are considered those that by their scope or form of execution do not conform to what is defined by the National Council of Tax Benefits based on international manuals. Below is an enunciative list of this type of projects:

  • Projects that due to their scope, structure and results can be considered as Scientific Research or Technological Development.
  • Projects that consist essentially in the contracting of technological services and / or specialized consultancies.
  • Routine efforts (50) to improve the quality of products.
  • The adaptation of an existing product or production process to the specific requirements imposed by a customer (Custom production). Unless they imply significantly different functional attributes.
  • The periodic or seasonal changes (eg, fashion design).
  • Design changes or aesthetic modifications that do not alter the functionality of the product or existing products.
  • Marketing of products and services of other companies, including parent companies.
  • Routine adjustments made by the company due to its normal operation or leveling with respect to competitors that do not involve developments by the company.
  • Increases in production or service capacity, due to the increase in production capacity or the use of logistics systems similar to those currently used by the company. (Projects to increase production or service capacity that have not been derived from R & D processes or activities 51
  • Changes in business practices, work organization or external relationships that are based on organizational methodologies already used by the company.
  • Projects of organizational innovation that do not imply the introduction of new organizational methods or that have been previously used by the company.
  • Projects whose main focus is the application or contracting of existing methodologies, for example: competitions, challenges, methodology for closing gaps, among others.
  • Mergers, acquisitions and / or similar operations, for example: transformation, asset purchase, spin-off, etc.
  • The acquisition and simple parameterization of software for business management (ERP – CRM).
  • The projects whose main objective are:
  • Prefeasibility studies52, feasibility53.
  • Hiring of technological services and / or specialized technicians.
  • Administrative and legal activities aimed at obtaining intellectual property products
  • Management and indirect support activities that do not constitute R & D in themselves.
  • Consulting activities
  • The replacement, purchase, expansion or update of infrastructure, machines, equipment or computer programs.
  • Strengthening of institutional capacities derived from routine activities of the company.
  • Commercial application software and development of information systems using known methods and existing computer tools
  • Adaptation and / or purchase of software for the integration of other existing systems.
  • The maintenance of existing computer systems.
  • The conversion or translation of computer languages.
  • The addition of user functions to those of computer applications.
  • The adaptation of existing software.
  • The preparation of documentation for the user.
  • The unique development of a digital application (app) or customization of an existing digital application.

Those developed in Free Trade Zones based on the simple fulfillment of the Master Plan for General Development of the Free Trade Zone.

Those that are developed based on simple compliance with current regulations and / or obtaining certifications.

2.3.3. Content requested for the evaluation of an Innovation project.

In order to carry out the proposal evaluation process, the technical secretariat of the National Tax Benefits Council has defined a series of contents requested in the online form for the registration of projects. Below is each of these contents with their respective description to guide proponents and / or evaluators in the process of qualifying the proposals as CTeI projects.

2.3.4 Criteria for qualification of an Innovation project.

Pertinence of the Project: (50%), it will be evaluated that:

The proposal is duly formulated and the proposed activities point to the solution of previously identified needs. In the proposal, there is a clearly identified market with its economic and social impacts, compared to: potential customers, final and direct users, estimates of the volume of additional revenue or market share that the company can obtain. In the case of innovations in process and organizational, the company has identified and quantified the cost savings or the impact in terms of performance variables, positioning or quality attributes that will bring the implementation of innovation to the company.

The scientific, professional or interdisciplinary staff (for example, technicians, commercial experts, financiers, researchers, etc.), has experience in the scope of application of the project and has been immersed in other innovation processes or has had experience in the development of projects of impact in the sector linked to the proposal. The knowledge, technical or verifiable professional trajectory related to the theme of the submitted proposal must be assessed.

The company has the capacity of infrastructure and equipment necessary for the development of the project and to allocate the necessary resources for its successful execution.

The support staff defined in the project is sufficient to perform the tasks assigned within the project.

There is coherence between the time spent by the work team and the activities to be developed.

There is coherence between the proposal and the administrative and technical management capacity of the group, center, R & D unit recognized or the researcher who co-executes or supervises the project to be qualified.

The distribution of budgeted resources in the project is coherent and sufficient. It will be verified that the budgeted items are necessary for the achievement of the objectives, are clearly defined, justified in the proposal and conform to the project type document.

The innovation proposal has previous developments or background that provide support to the proposed solution and contains novel elements that have not been implemented or developed previously by the company and that aim to generate competitive advantages.

Quality of the project: (30%), it will be verified:

There is coherence between the description of the problem or need, the state of the art, the challenge or opportunity to be addressed and the objectives of the project.

The results of the project point to the scaling of results of previous stages of research or innovation that lead to the incorporation of innovation in the market and / or implementation of the solution in the company.

The proposed solution presents a degree of novelty and added value, to address the opportunity; the technological or non-technological challenges to be solved; or it generates changes of positioning in the market that the company would have given the execution of the project.

The methodology proposed allows the obtaining of results, the scope of the general objective and responds to the nature of an innovation project.

The innovation contains theoretical or practical foundations that give viability to the development of the project and satisfaction of an identified need.

Within the postulated project, there are activities that allow the appropriation of the knowledge generated by the company, the sector and / or country, or the patent application on the obtained innovation.

Impact of the project. (20%) It will be verified:

There is a clearly identified strategy within the company to capture the value added by innovation.

The development of the project, will bring as a result an innovation for the company, the sector, the region, the country or internationally.

The economic, social, technological, environmental and cultural impact of innovation has been identified and quantified and is considered significant compared to the identified problem.

The contribution to strengthening the competitiveness of companies and the productive sector.

NOTE: The minimum qualification for the approval of a project will be 80 points.

3. Financeable items for CTeI projects

The National Council of Tax Benefits has defined as items that can access tax benefits for investment in Science, Technology and Innovation projects, which are shown below:

SCIENTIFIC PERSONNEL

This item includes the fees paid to scientific personnel. These personnel carry out direct activities of Science, Technology and Innovation in the project aimed at achieving the objectives. Remember that only the values described in this item may access Non-Constituent Income from income and / or occasional gain. (More information see section 4.2.)

Fees paid to support staff, administrative staff related to the proposal and personnel not involved in the project.

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4. Roles in the projects of CTeI4.1. Roles of the entities participating in the project

The entities participating in the postulated projects, depending on the functions and tasks assigned, will have one of the following roles:

Executor: Any mixed or private company or natural person, who technically and financially leads the project and is responsible for carrying out the fulfillment of the objectives and results proposed for the CTeI project and the investments registered in the SIGP. There can only be one executing agency in the project and it must be a taxpayer of income.

Co-executor: Any company, public or private institution, that participates directly in the fulfillment of the objectives and results proposed for the CTeI project, under the direct or indirect coordination of the executor. Co-executors can participate with different income taxpayers of the executing agency who participate and invest in the execution of the project, as well as a research group or center, research centers and institutes, technological development centers, Science Technology parks and Innovation, Research Results Transfer Offices (OTRI), innovation and productivity centers, technology-based incubators, science centers and organizations that promote the use and appropriation of science, technology and innovation that will be part of the development of the project.

Technical Supervisor: Natural or legal person who exercises a specialized technical activity, and whose fundamental purpose is to guide, support and ensure compliance with scientific, technical and budgetary commitments throughout the life cycle of the CTeI project. Every supervisor must have the recognition of Colciencias as a research group or center, research centers and institutes, technological development centers, Science Technology and Innovation parks, Research Results Transfer Offices (OTRI), innovation and productivity centers , technology-based incubators, science centers and organizations that promote the use and appropriation of science, technology and innovation, with expertise in the thematic area of project development and that will endorse the project they will present.

If a change of the actor recognized by Colciencias is required, the proponent must request COLCIENCIAS the approval of the new entity that will endorse the project, for which COLCIENCIAS will verify the suitability based on the information registered in the ScienTI platform or Colciencias own databases.

4.2. Roles of the staff in the project

The project personnel are the people who work directly and indirectly in the conception or creation of new knowledge, products, processes, services, methods and systems, 54 and can have the following roles:

SCIENTIFIC PERSONNEL: These are the people who carry out direct CTeI activities that require the application of concepts, design of methodologies, validation of results and are in charge of coordinating and controlling the execution of the project. These personnel perform tasks directly related to the main activities of the project, and have verifiable technical and / or professional expertise in the development of CTEI projects and / or in the main thematic area of the proposal. This category includes the Principal Investigator, researcher Company of the productive sector, Co-researcher, Software Developer and advisor.

Principal Investigator: Is the director or leader of the life cycle of the project. It directly develops activities of planning and management of the scientific and technical aspects of the work of the co-researchers, among its main tasks are the formulation, execution and technical coordination for the development of the objectives and achievement of the proposed results. It has the technical capacity and accredited expertise in the thematic area of the project to be developed. For purposes of software development projects, the principal investigator will be the one responsible for the software life cycle. In the case of personnel associated with the companies, the principal investigator will be the professional with experience in the development of research and / or innovation projects.

The principal investigator will be in charge of approving personnel changes and transfers between items approved by the CNBT without exceeding 20% of the total value of the fiscal period and report them to COLCIENCIAS in the annual technical and financial execution report. When for some reason it is required to change the principal investigator of the project, you must request it from COLCIENCIAS by sending the resume of the new principal investigator who must have an equal or superior profile, when in the framework of the project they do not have an equal or superior profile, the entity must send a summary of the resumes of the scientific personnel to COLCIENCIAS and request the designation of the principal investigator.

It is necessary to designate a principal investigator for each project and must be linked to the project throughout the life cycle and have a time commitment according to the defined functions.

Co-researcher: Thematic expert who contributes and technically and operationally supports the activities of CTeI during the life cycle of the project. Participate directly from your field of expertise. Doctoral or master’s degree students who are directly linked to the execution of the project are included in this category. In the case of companies, it consists of technical or professional personnel specialized in the thematic areas where the project is developed, an example of this may be the production manager or the supervisor of a production line in an automotive or food factory.

Researcher of the Productive Sector: Person who, due to his / her academic training and / or professional experience, has the knowledge related to the system or topics

intervene and participate actively in the development of the project, technically and operationally supporting the activities to be executed.

Software developer: Person who, due to his training and experience, actively participates in one or more aspects of one or several stages of the software development cycle and technically and operationally supports the activities of the project to be executed.

Advisor: Consultant or counselor of an external nature to the participating entities, expert in the subject, and whose services are contracted given their expertise in the topic of the CTeI project. Your contributions are required for the development of the project, therefore you must clearly identify the specific deliverables of your advice. This advisor can be national or international.

SUPPORT PERSONNEL: These are the people who carry out indirect activities of CTeI that require the application of concepts and operational methods, under the supervision of scientific personnel. This category includes research assistants, field staff, laboratory support personnel, operators, technicians, and students in general.

Their tasks include among others:

  • Perform bibliographic searches and select material and relevant information in archives and libraries.
  • Perform validation tests of the first versions of software
  • Perform experiments, tests and analysis.
  • Prepare the materials and equipment necessary for conducting experiments, tests and analysis.
  • Record data, make calculations and prepare tables and graphs related to the project.
  • Conduct statistical surveys and interviews necessary for the project. 

ADMINISTRATIVE PERSONNEL: These are the people who perform administrative support activities for the development of a CTeI project. Included in this category are financial, security, general services, managers or project coordinators with project management functions without deepening the design of the research or the validation of results.

5. Typology of products as results of CTeI activities

Products resulting from Generation of New Knowledge activities

Research articles A1, A2, B and C

Articles in indexed journals, in the indices and bases mentioned in the group measurement model.

Research articles D

Articles in indexed journals, in the indices and bases mentioned in the group measurement model.

Research result books

Books that meet the minimum quality requirements specified in the group measurement model.

Chapters in book result of research

Chapters in research results books, which meet the minimum quality requirements defined in the group measurement model.

Technological products patented or in the process of granting the patent

Patent obtained or requested via PCT or traditional and utility model, which meet the requirements defined by the group measurement model.

Vegetable variety and animal variety

Must meet the quality requirements of the group measurement model.

Products resulting from Technological Development & Innovation activities

Certified or validated technological products

Industrial design, integrated circuit scheme, software, pilot plant, industrial prototype and distinctive signs that meet the requirements of the group measurement model.

Regulations, rules, regulations or legislations

Regulations, norms, regulations, legislations, clinical practice guides and differentiated bills according to the scope of application (national and international), that meet the requirements of the group measurement model.

Business Products

Business secret, technology-based companies (spin-off and start-up), creative and cultural industries, innovations generated in business management, innovations in processes, procedures and services that meet the requirements of the group measurement model.

Scientific-technological consultancies and final technical reports

Scientific-technological consultancies and final technical reports; and consulting in art, architecture and design, which meets the requirements of the group measurement model.

License agreements for the exploitation of works protected by copyright

License agreements for the exploitation of works protected by copyright, which complies with the requirements of the group measurement model.

Products resulting from activities of Social Appropriation of Knowledge

Citizen participation in CTEI

Citizen participation or community (s) in research projects. Space / event of citizen or community participation (s) related to the CTeI, which meets the requirements of the group measurement model.

Pedagogical strategies for the promotion of the CTEI

Program / Pedagogic strategy to promote the CTEI. It includes the formation of networks to promote the social appropriation of knowledge, which meets the requirements of the group measurement model.

Social communication of knowledge.

Knowledge communication strategies, generation of printed, multimedia and virtual contents, that meets the requirements of the group measurement model.

Circulation of specialized knowledge

Scientific events and participation in knowledge networks, creation workshops, cultural and artistic events, working papers, informative bulletins of research results, scientific journal editions or books resulting from research and final research reports, meet the requirements of the group measurement model.

Acknowledgments

Awards or distinctions granted by institutions, public or private organizations that use parameters of excellence to recognize management, productivity and contributions and the impact of research or technological development in an area of knowledge.

Products of activities related to the Training of Human Resources for the CTEI

Doctoral thesis

Management or co-direction or advising of Doctoral Thesis, theses are differentiated with recognition of those approved. These products must meet the requirements of the group measurement model.

Master’s degree work

Management or co-direction or consultancy of work of master’s degree, works are differentiated with recognition of those approved. These products must meet the requirements of the group measurement model.

Undergraduate work

Management, co-direction or advice of work of undergraduate degree, work is differentiated with recognition of those approved. These products must meet the requirements of the group measurement model.

Research and Development Projects

Projects executed by the Research Groups as Principal Investigator classified according to funding sources. These products must meet the requirements of the group measurement model.

Research projects – Creation

Projects executed by the research groups in their capacity as principal investigator, classified according to funding sources. These products must meet the requirements of the group measurement model.

Research, Development and Innovation Projects (R + D + I)

Projects executed by researchers in companies and projects with young researchers in companies. These products must meet the requirements of the group measurement model.

Extension and social responsibility project in CTEI

Extension projects, in which the type of participation of the research group in the project is specified (extension project in CTEI or social responsibility project – solidarity extension). These products must meet the requirements of the group measurement model.

Support for training programs

Support for the creation of master’s or doctorate programs or courses. These products must meet the requirements of the group measurement model.

Accompaniment and advising of thematic lines of the Ondas Program

Accompaniments and advice on thematic lines of the Ondas Program. These products must meet the requirements of the group measurement model.

Annex 1: Software Project

DEFINITION OF SOFTWARE56: “A software product is the sum total of the computer programs, procedures, rules, technical documentation and associated data that are part of the operations of a computer system.”

It includes among others:

  1. Several independent computer programs. 
  2. Configuration files that are used to execute these programs. 
  3. A documentation system that describes the structure of the system. 
  4. The documentation for the user that explains how to use the system. 
  5. Websites that allow downloading information on recent products57.

SOFTWARE DEVELOPMENT58: “In order for a software development project to be classified as R & D, its realization must lead to scientific or technical progress and its objective must systematically resolve a scientific or technical uncertainty.

The development of the software in the projects can be classified in R & D whenever there is an advance in the field of information technology.

Normally, these advances are generally evolutionary rather than revolutionary. Therefore, upgrading to a more powerful version, improving or modifying an existing program or system, can be classified as R & D if they provide scientific and / or technological progress that leads to greater knowledge “(.. .)

LOGICAL SUPPORT

The software consists of one or more of the following elements: the computer program, the program description and the auxiliary material.

For the purposes of the previous article, it is understood as:

a) “Computer program”: The expression of an organized set of instructions, in natural or coded language, regardless of the medium in which it is stored, whose purpose is to make a machine capable of processing information, indicate, perform u obtain a function, a task or a specific result.

b) “Program description”: A complete presentation of procedures in a suitable form, sufficiently detailed to determine a set of instructions that constitute the corresponding computer program.

“Auxiliary material”: Any material, other than a computer program or a program description, created to facilitate its understanding or application, such as description of problems and instructions for the user. … “

APPLICATION DOMAINS OF THE SOFTWARE

Currently, there are seven major software categories:

Systems software: Set of written programs to service other programs. Certain systems software (for example, compilers, editors, and tools for managing files) processes complex but deterministic information structures. Other applications of systems (for example, components of operating systems, drivers, network software, telecommunications processors) process mostly indeterminate data. In any case, the systems software area is characterized by: great interaction with the computer hardware, intensive use by multiple users, concurrent operation that requires sequencing, shared resources and administration of a sophisticated process, complex structures of data and multiple external interfaces.

Application software: Isolated programs that solve a specific business need. Applications in this area process commercial or technical data in a way that facilitates business operations or administrative or technical decision making. In addition to conventional data processing applications, application software is used to control real-time business functions (for example, point-of-sale transaction processing, real-time manufacturing process control).

Engineering and science software: It has been characterized by algorithms “devourers of numbers”. Applications range from astronomy to volcanology, from stress analysis in automobiles to the orbital dynamics of the space shuttle, and from molecular biology to automated manufacturing. However, modern applications within the area of engineering and science are abandoning conventional numerical algorithms.

Computer-aided design, system simulation and other interactive applications have begun to be done in real time and have even taken on system software features.

Embedded Software: Resides within a product or system and is used to implement and control features and functions for the end user and the system itself. Embedded software performs limited and particular functions (for example, control of the panel of a microwave oven) or provides significant operational and control capability (digital functions in a car, such as fuel control, control panel and control). braking systems).

Product line software: It is designed to provide a specific capacity for use by many different consumers. The product line software focuses on a limited and particular market (for example, product inventory control) or is directed to mass consumer markets (word processing, spreadsheets, computer graphics, multimedia, entertainment, database management and applications for personal or business finances).

Web applications: Called “webapps”, this category of network-centric software groups a wide range of applications. In its simplest form, webapps are little more than a set of linked hypertext files that present information with limited text and graphics. However, since the emergence of Web 2.0, webapps are evolving into sophisticated computing environments that not only provide isolated features, computing functions and content for the end user, but are also integrated with corporate databases and business applications.

Artificial intelligence software: It makes use of non-numerical algorithms to solve complex problems that are not easy to treat computationally or with direct analysis. Applications in this area include robotics, expert systems, pattern recognition (image and voice), artificial neural networks, theorems and games demonstration.

STAGES FOR THE DEVELOPMENT OF SOFTWARE61

The development of the Software includes the following stages62:

Analysis stage: Process in which the requirements of the system are defined, by the precision of its functions, its behavior, degree of performance, the architecture to be used and the integration with other systems. You can refer to the Software Requirements (ERS) specification as defined in the IEEE 830 standard.

Design stage: Process in which the definition and description of the information model is carried out, the modules that make up the architecture, the characteristics of the user interface and the procedural detail (algorithms) of the software, in accordance with the defined specifications In the analysis. You can refer to standard such as UML.

Implementation stage: Process in which the translation of the design is carried out in source code and the tests for the detection of errors in the developed code.

Validation and verification stage: Process in which tests are carried out to verify compliance with the requirements and acceptance by the end user.

Annex 2: Additional score awarded for participating in programs and strategies defined by the CNBT.

The National Council of Tax Benefits (CNBT) with the purpose of encouraging private investment in Science, Technology and Innovation projects, approved in the sessions held on July 30, December 17, 2015 and September 28, 2017, according to in minutes 2 and 3 of 2015 and minutes 3 of 2017, give an additional score to the projects presented by companies that participate in the programs and / or strategies defined by the CNBT, which are shown below:

PACT FOR INNOVATION 

The companies that sign the Pact for Innovation and that are part of the Systems for

Innovation, you will obtain a total of 5 additional points in the global qualification of the project.

ASSOCIATION BETWEEN USERS OF BENEFIT AND SMES.

In order to promote the association between user companies of the tax benefit and SMEs, the CNBT will award an additional score in the global rating of the project to those entities that involve SMEs as co-executors, granting the projects a score in a range of 1 to 5 according to the following criteria approved by the CNBT:

PROJECTS THAT CONTRIBUTE TO THE GOALS OF THE OBJECTIVES OF SUSTAINABLE DEVELOPMENT PRIORITIZED BY THE CNBT.

The projects presented by companies that, within their formulation and results, contribute to the fulfillment of the goals established within the sustainable development objectives shown below, will obtain a total of 10 points in the overall project rating. The technical evaluators will define in the qualification of the project, if they award the additional score to the presented proposal.

Ending poverty

  • Appropriation and access to new technologies for populations in situations of poverty and vulnerability.
  • Promote the resilience of the poor and people in vulnerable situations and reduce their exposure and vulnerability to extreme events related to climate and other economic, social and environmental crises and disasters.

Hunger and food security

  • Duplicate agricultural productivity and income of small-scale food producers, particularly women, indigenous peoples, family farmers, pastoralists and fishermen, including through secure and equitable access to land, to others production and input resources, knowledge, financial services, markets and opportunities for the generation of added value and non-agricultural jobs.
  • Sustainability of food production systems and resilient agricultural practices that increase productivity and production, contribute to the maintenance of ecosystems, strengthen the capacity to adapt to climate change, extreme weather events, droughts, floods and other disasters, and progressively improve the quality of soil and soil.
  • Maintain the genetic diversity of seeds, cultivated plants and farm and domesticated animals and their related wild species, inter alia through good management and diversification of seed and plant banks at the national, regional and international levels, and promote access to the benefits derived from the use of genetic resources and traditional knowledge and their fair and equitable distribution.
  • Increase investments in rural infrastructure, agricultural research and extension services, technological development and gene banks of plants and livestock in order to improve agricultural production capacity.
  • Adopt measures to ensure the proper functioning of food commodity markets and their derivatives and facilitate timely access to information on markets, in particular on food reserves, to help limit the extreme volatility of food prices. 

Health

  • Reduce the maternal mortality rate and put an end to the avoidable deaths of newborns and children under 5 years of age.
  • End the epidemics of AIDS, tuberculosis, malaria and neglected tropical diseases and combat hepatitis, waterborne diseases and other communicable diseases.
  • Reduce premature mortality from noncommunicable diseases through prevention and treatment and promote mental health and well-being.
  • Strengthen the prevention and treatment of the abuse of addictive substances, including the misuse of narcotics and the harmful consumption of alcohol.
  • Reduce deaths and injuries caused by traffic accidents in the world.
  • Guarantee access to sexual and reproductive health services, including family planning, information and education, and the integration of reproductive health into national strategies and programs.
  • Achieve health coverage, in particular protection against financial risks, access to quality essential health services, and access to safe, effective, affordable and quality medicines and vaccines for all.
  • Substantially reduce the number of deaths and diseases caused by hazardous chemicals and the pollution of air, water and soil.
  • Strengthen the application of the Framework Convention of the World Health Organization for Tobacco Control.
    Support the research and development of vaccines and medicines for communicable and noncommunicable diseases that affect the population and facilitate access to essential medicines and vaccines.
  • Strengthen the country’s capacity for early warning, risk reduction and risk management for national health

Education

  • Substantially increase the number of young people and adults who have the necessary skills, particularly technical and professional, to access employment, decent work and entrepreneurship.
  • Eliminate gender disparities in education and ensure equal access for vulnerable people, including persons with disabilities, indigenous peoples and children in situations of vulnerability, at all levels of education and vocational training .
  • Ensure that all young people and at least a substantial proportion of adults, both men and women, have reading, writing and arithmetic skills.
  • Gender equality and empowerment of women.
  • Guarantee access to sexual and reproductive health and reproductive rights.
  • Undertake reforms that grant women the right to economic resources under equal conditions, as well as access to property and control of land and other assets, financial services, inheritance and natural resources, in accordance with national laws
  • Improve the use of instrumental technology, particularly information and communication technology, to promote the empowerment of women.

Clean water and basic sanitation

  • Achieve equitable access to adequate sanitation and hygiene services for all and put an end to open defecation, paying special attention to the needs of women and girls and people in vulnerable situations
  • Improve water quality by reducing pollution, eliminating dumping and minimizing the discharge of hazardous materials and chemicals, halving the percentage of untreated wastewater and substantially increasing recycling and reuse in safety conditions worldwide
  • Substantially increase the efficient use of water resources in all sectors and ensure the sustainability of the extraction and supply of fresh water to cope with water scarcity and substantially reduce the number of people suffering from water scarcity.
  • Implement the integrated management of water resources at all levels.
  • Protect and restore ecosystems related to water, including forests, mountains, wetlands, rivers, aquifers and lakes.
  • Capacity-building in activities and programs related to water and sanitation, including water storage and storage, desalination, efficient use of water resources, wastewater treatment, and recycling and reuse technologies.
  • Support and strengthen the participation of local communities in the improvement of water management and sanitation.

Energy

  • Guarantee access to affordable, reliable and modern energy services.
  • Substantially increase the percentage of renewable energy in the set of energy sources.
  • Improve the rate of energy efficiency.
  • Improve technology to provide modern and sustainable energy services.

Economic growth

  • Achieve higher levels of economic productivity through diversification, technological modernization and innovation, among other things by focusing on sectors with higher added value and labor-intensive use.
  • Improve the efficient production and consumption of natural resources and seek to dissociate economic growth from environmental degradation.
  • Promote sustainable tourism that creates jobs and promotes local culture and products.
  • Resilient infrastructures.
  • Readjust industries to be sustainable, using resources more effectively and promoting the adoption of clean and environmentally sound technologies and industrial processes.

Resilient and sustainable cities

  • Provide access to safe, affordable, accessible and sustainable transport systems for all and improve road safety, in particular through the expansion of public transport, paying special attention to the needs of vulnerable people, women, children, people with disabilities and the elderly.
  • Increase inclusive and sustainable urbanization and capacity for participatory, integrated and sustainable planning and management of human settlements.
  • Significantly reduce the number of deaths and people affected by disasters, including those related to water, and substantially reduce the direct economic losses linked to the global gross domestic product caused by disasters, with a particular emphasis on the protection of poor people and people in vulnerable situations.
  • Reduce the negative environmental impact per capita of cities, including paying special attention to air quality and the management of municipal and other types of waste.

Responsible production and consumption

  • Achieve sustainable management and efficient use of natural resources.
  • Reduce food losses in the production and distribution chains, including post-harvest losses.
  • Achieve environmentally sound management of chemicals and all wastes throughout their life cycle, and significantly reduce their release to the atmosphere, water and soil in order to minimize their adverse effects on the environment. human health and the environment.
  • Adopt sustainable business practices and implement more sustainable modes of consumption 
  • and production based on scientific and technological knowledge.

Climate change

  • Strengthen resilience and the ability to adapt to risks related to climate and natural disasters in all countries.
  • Incorporate measures related to climate change into national policies, strategies and plans.
  • Increase effective planning and management capacity in relation to climate change.

Oceans and underwater life.

  • Prevent and significantly reduce marine pollution of all kinds, particularly pollution caused by activities carried out on the mainland, including marine debris and contamination by nutrients.
  • Managing and sustainably protecting marine and coastal ecosystems with a view to avoiding significant adverse effects, including by strengthening their resilience, and taking measures to restore them in order to restore the health and productivity of the oceans.
  • Minimize the effects of ocean acidification and address them, including through the intensification of scientific cooperation at all levels.
  • Restore fish stocks in the shortest time possible, at least at levels that can produce the maximum sustainable yield according to their biological characteristics.
  • Increase scientific knowledge, develop research capacity and transfer marine technology, in order to improve the health of the oceans and enhance the contribution of marine biodiversity to the development of society.
  • Improve the conservation and sustainable use of the oceans and their resources.

Forests, desertification and ecological diversity.

  • Conservation, restoration and sustainable use of terrestrial ecosystems and inland freshwater ecosystems and the services they provide, in particular forests, wetlands, mountains and arid zones, in line with obligations undertaken under international agreements.
  • Promote the sustainable management of all types of forests, put an end to deforestation, recover degraded forests and increase afforestation and reforestation
  • Fight against desertification, rehabilitate degraded lands and soil, including lands affected by desertification, drought and floods.

World Alliance for Sustainable Development

Promote the development of environmentally sound technologies and their dissemination and dissemination.

The total sum of the score awarded in any case may exceed ten points. Entities may only access one of these modalities to obtain additional points.

Annex 3. Conceptualization of SNCTeI actors according to the TRL.

The level of technological maturity or TRL (Technology Readiness Level for its acronym in English), is a tool that as defined in the National Policy Document on Science, Technology and Innovation (CTeI) No. 1602 allows the identification of the actors that they make up the National System of CIII classified by the development of their main activities. The TRL is a methodology that allows to identify the recognized actors that can endorse the proposals according to the orientation and thematic expertise that each one possesses.

Bearing in mind that there is no linear relationship between the R & D & I projects, an approximation to the equivalence between the typology of projects and the TRLs is shown below:

In the previous graph, the Experimental Development typology is located in TRL 4 and 5, since they are small-scale laboratory designs in the laboratory and / or simulated environment close to the real one. The definition of each level of technology maturity is shown below based on what is presented in the Technical self-assessment guide for the recognition of the company’s R + D + i unit:

TRL 1 – Basic principles observed and reported: This corresponds to the lowest level in terms of technological maturity level. At this level, basic scientific research begins and the transition to applied research begins. The descriptive tools can be mathematical formulations or algorithms. At this stage of development there is still no degree of commercial application.

TRL 2 – Technology concept and / or formulated application. Applied research. The theory and scientific principles are focused on specific areas of application to define the concept. In this phase, possible applications of theoretical-level technologies and analytical tools for simulation or analysis can begin to be formulated. However, there is still no evidence to validate this application.

TRL 3 – Concept tests of analytical and experimental characteristics. This phase includes the carrying out of research and development (R & D) activities, which include the performance of analytical tests, concept tests or laboratory-scale, aimed at demonstrating the technical feasibility at the theoretical level of technological concepts. This phase involves the validation of the components of a specific technology, although this does not result in the integration of all the components in a complete system.

TRL 4 – Validation of components / subsystems in laboratory tests. In this phase, the components that make up a certain technology have been identified and it is sought to establish if these individual components have the capabilities to act in an integrated manner, working together in a system.

TRL 5 – Validation of systems, subsystems or components in a relevant environment (or industrially relevant in case of key enabling technologies). The basic elements of a certain technology are integrated so that the final configuration is similar to its final application. However, the operability of the system and technologies still occurs at the laboratory level.

TRL 6 – Validation of system, subsystem, model or prototype in close to real conditions. In this phase it is possible to have pilot prototypes capable of developing all the necessary functions within a given system, having passed feasibility tests in real operating or operating conditions. It is possible that components and processes have been expanded to demonstrate their industrial potential in real systems. The available documentation may be limited.

TRL 7 – Demonstration of validated system or prototype in the real operating environment. The system is or is about to operate on a pre-commercial scale. It is possible to carry out the identification phase of aspects related to manufacturing, life cycle assessment, and economic evaluation of technologies, with most of the functions available for testing. The available documentation may be limited.

TRL 8 – Complete and qualified system through tests and demonstrations in operational environments. In this phase, the systems are integrated, the technologies have been tested in their final form and under assumed conditions, having reached in many cases, the end of the development of the system. Most of the available documentation is complete.

TRL 9 – System tested and operating successfully in a real environment. Technology / system in its final phase, tested and available for commercialization and / or production.