with terminology, theoretical approaches and relevant viewpoints on technology. This theoretical knowledge is important for understanding how an idea materializes and to grasp the potential of its dissemination within society. Especially for an emerging field such as care robotics, it helps to understand the ongoing process. Additionally, it might offer opportunities to influence the future field in the desired direction. For this study, an extensive knowledge of the theoretical field is essential for subsequent analysis (see Chapter 6) of several care robot projects. In the course of this, the focus lies in particular on the initial idea, development process and implementation.
Charles Darwin defined evolution from a biological perspective as the development and adaptation of a species to their natural environment. For several decades in technology studies, Darwinian beliefs also prevailed in understanding the success of inventions (see Figure 2-1). At first glance, technological development and innovation seem to be subject to a linear evolution-like process, because they seem to be simple adaptations of tech-nical possibilities and user demands. A century after Darwin, Mokyr (1990, 273–74) points out: “the analogy [of biological evolution] is useful for understanding the dynamic aspects of technological progress. In particular, it can be used to answer the question whether or not technological progress took place in small incremental steps or large leaps.” By making use of this analogy, technological change is understood as a rather continuous process that builds more on temporal logic than an abrupt process with shortcuts. It makes sense to rely on biological evolution terminology because it helps to get a better basic understanding of the complexity of technology. For this reason, many scholars used and still use the biological term ‘evolution’ as a metaphor or tool to illus-trate technology development (Braun-Thürmann 2005, 42). In other words, the term bi-ological evolution sheds a first light on the multi-faceted transition of a first vague idea into a finished commercialized invention. This simplification applies to care robots as well, with an engineer’s idea at the beginning which has to be transformed into an artifact.
Figure 2-1 The Traditional and Modern View on the Production of Technical Knowledge
The invention2 of a new artifact, product or other kind of technical knowledge can be divided into four simple stages (see Figure 2-1): Discovery, invention, development and diffusion (Braun-Thürmann 2005, 36–37). First, a promising idea is picked (stage of dis-covery) out of a pool of various ideas and basic research is initiated. Second, selective application-oriented research is pursued (stage of invention), which often ends with the registration of a patent. Third, in the transfer stage of development, an idea is designed into a commercial product. Finally, the invention is available on the market (stage of diffusion) and context of use is developed within society, which means the users decide about adoption or rejection.
However, the main weakness of evolutionary (see Figure 2-1) approaches has been substantially critiqued by Dierkes, Hoffmann, and Marz (1996, 34), who argue that “the
‘best’ technical solutions survive and the ‘poor’ ones do not. Conventionally, the history of technology is therefore presented as a chronicle of ‘technological victors’”. Similar to Darwin’s evolution theory, technology also becomes a survival of the fittest, which quickly forgets the losers. However, there is the risk of imagining innovation as an “evolutionary mechanism of technological inception” (Dierkes, Hoffmann, and Marz 1996, 33). Fergu-son (1974, 19) states that “the whole history of technological development had followed an ordered or rational path, as though today’s world was the precise goal toward which all decisions, made since the beginning of history, were consciously directed”. In the end, this means that a linear evolutionary approach can only highlight successful and finished technologies.
Wiebe E. Bijker, Hughes, and Trevor J. Pinch (1987, 406) take this a step further, when they criticize the evolutionary approaches, because “[they] rely on the manifest success of the artifact as evidence that there is no further explanatory work to be done.” Not implemented and unsuccessful technologies remain forgotten. Even more, successful inventions are not the only possible ones. In many cases, there are alternatives to the prevailing inventions. One example is the QWERTY keyboard (Braun-Thürmann 2005, 51), which is the dominant keyboard, even if more user-friendly alternatives exist, but never prevailed in the end.
In this context, another relevant limitation of the evolutionary perspective on technology becomes clear: Technology is often understood as a neutral, not moral, instrument. The utilization of the instrument makes a positive or negative invention out of it. In doing so,
2 The terms artifact, invention, innovation, technological knowledge or product are regarded as interchange-able.
the responsibility for any technology assessment is pushed onto its utilization (Gleits-mann-Topp, Kunze, and Oetzel 2009, 35). The advantage of such a viewpoint lies in its simplicity to make the untransparent process of technology development accessible. Ac-cording to this viewpoint, which is rather associated with technological determinism, tech-nology development is seen as independent from society, which leaves the influence of the user on technology unconsidered. For instance, one may use a knife as a kitchen tool for cooking or as a tool to injure people. Technological determinism pushes the re-sponsibility for the consequences of technology onto the society which is utilizing it.
Dierkes, Hoffmann, and Marz (1996, 33) argue that “the history behind the emergence of these artifacts […], however, [is often] forgotten in the finished products.” Adequately, theoretical concepts have to offer analytic solutions (see Chapter 3) able to include al-ternative unsuccessful inventions as well. Otherwise, it is not possible to structurally cap-ture current emerging fields, such as care robotics, with a theoretical framework. One of the characteristics of emerging fields is that the prevailing state of the art develops out of a process, with many unsuccessful inventions or ideas which never make it to the prototype stage. This process is dominated by trial and error. In other words, there is a danger that technology studies limit themselves to success and its reconstruction. It is not important to explain the success; it is important to explain the process.
For this reason, theoretical studies on technology have to address the relevant and crit-ical impact factors of the process on technology development, which is fundamental for capturing the process of innovation in its full complexity. This study fulfils this responsi-bility through a two-step approach. First, a vocabulary from the STS is built up in order to capture the process of technology development and second, this vocabulary is inter-laced into a theory, namely the concept of vision, to get an analytic tool to work with.
2.2 The Paradigm Shift to a Participatory Understanding of Technology Devel-opment
Already in the fifties, anthropologist Arnold Gehlen (1957, 9) mentioned the dependence of technology on human beings: “The world of technology is, so to speak, the <great human>: Ingenious and tricky, life-supportive and life-disrupting like himself, with the
same broken relationship to nature. It is, like humans, <nature artificielle>.”3 Every tech-nology is not only artificial by itself, but also depends on human beings, because without humans there would be no technology. Having said this, there has not been enough consideration to the circumstance that technology does not develop by itself. Mokyr (1990, 151) also argues that a technology-centered perspective provides an inaccurate approach to the reality of the emergence of technology, because “the ‘demand’ for tech-nology is a derived demand, that is, it depends ultimately on the demand for the goods and services that technology helps produce; there is little or no demand for technology for its own sake.” In other words, new technologies are embedded into a complex social setting rather than emerging in a vacuum. This can be summarized with Braun-Thür-mann’s (2005, 6) definition of innovation. According to this, “innovations can be de-scribed as material or symbolic artifacts, that observers perceive as new and experi-enced as an improvement to the existing.”4 This means that innovations are interactive objects produced artificially through social interaction and also, once emerged, become utilized through a specific social adaption. Thereby the needs of society are the major impact factor for the successful development of technology and its overall use within society. When having a closer look at various care robot projects (see Chapter 6), I pre-sume that the ones which were developed according to the user’s needs are the ones which will prevail in the long-term.
At this point, I want to recapitulate the contrary viewpoints of technological determinism and social constructionism5 to avoid misconceptions about development. Both have in common that they are dealing with technology and its genesis, progress and impact and break down the life cycle of technology, but each end in its own way. A major difference is that the former, technology determinism, indicates an understanding of technology
“according to that technology determines, through its consequences, the social, while it is itself not determined by the social, but follows an intrinsic logic outside of social factors.”
6 (Grunwald 2012, 55–56) Thereby technology is understood as something with a high
3 „Die Welt der Technik ist also sozusagen der <große Mensch>: geistreich und trickreich, lebenfördernd und lebenzerstörend wie er selbst, mit demselben gebrochenen Verhältnis zur urwüchsigen Natur. Sie ist, wie der Mensch, <nature artificielle>. “ (Gehlen 1957, 9)
4 „Als Innovation werden materielle oder symbolische Artefakte bezeichnet, welche Beobachterinnen und Beobachter als neuartig wahrnehmen und als Verbesserung gegenüber dem Bestehenden erleben.“ (Braun-Thürmann 2005, 6)
5 I want to make a short remark on the difference between social constructionism and social constructivism, because the familiarity of both terms can be confusing. The former understands artifacts as the result of social interactions. The latter focuses on the process resulting from the interaction of a single or multiple actors, giving no specific importance to the artifact.
6 „[…] danach determiniert die Technik durch ihre Folgen das Soziale, während sie selbst nicht durch das Soziale determiniert wird, sondern einer außerhalb gesellschaftlicher Einflussfaktoren liegenden Eigenlogik folgt.“ (Grunwald 2012, 55–56)
momentum, forcing society to adjust to it rather than being able to influence it. The latter sees technology development as a process, which is influenced by various actors and which sees technology as socially constructed. When focusing on emerging technologies, a social constructionist understanding of technology, according to which the innovation and its outcome is influenceable, fits better than technological determinism with innova-tion being an unchangeable process. This applies to care robots with their various rep-resentations as well, because they are an emerging field that is embedded in its target field of care, which in turn is strongly influenced by society and its needs.
Among the large number of theoretical approaches that deal with technology, the field of science and technology studies has especially to be mentioned, and it was established in the seventies. STS is not a single, but rather an interdisciplinary field, which is influ-enced by a variety of disciplines, in particular anthropology, psychology, and the political and social sciences (Niewöhner, Sörensen, and Beck 2012, 16). Within STS, many stud-ies focus on the relationship of technology and society, and related questions. In many cases, the above-mentioned technological determinism is questioned by having a closer look at the framework of technology development. STS theories can be subdivided into theoretical and active approaches (Sismondo 2008, 19–20). The former focus on the essence of technology, its definition and structure, its genesis and change as well as its connection to society. The main questions discussed are to which degree technology is dependent and how it affects society.
My study relies on terminology from the social construction of technology. SCOT deals with technology genesis as a social process. Thereby the critical factors for successful technology development are social factors, such as the consensus within a group or the construction of a common sense about the utilization of technology within society. In this context, the key concepts are the relevant social group and interpretative flexibility, which I will go into in detail later in this chapter (see Chapter 2.3).
However, for a better understanding of social constructionist perspectives on technology development, I give an overview of the main approaches, which is at the same time a short history of STS. Thereby the following, namely laboratory studies, actor-network theory and feministic STS approaches are set in relation to my study.
Laboratory studies, which emerged in the seventies, made scientific knowledge and technology approachable for analysis. Coming from a social constructionist perspective, laboratory studies focused on the micro-level within the generation process of new knowledge – the laboratory. In deviation from previous studies on technology, “what was
new was that they [laboratory studies] observed natural science in practice and de-scribed and analyzed the local modalities and forms of the production of natural science and knowledge in the laboratory in detail”7 (Amelang 2012, 145). In doing so, laboratory studies opened natural science and laboratories for the field of STS. and STS for natural science by making use of ethnographic methods. The so-called ‘black box’ (Latour and Woolgar 1986, 242) as the knowledge thinking process within the natural sciences had been seen and could be accessed by empirical research. The main question now was how scientists achieved their data and obtained their results, rather than questioning the validity of results. Such research has a lasting effect on the contemporary view of natural science as a specific knowledge culture.
Two publications particularly shaped laboratory studies with their ethno-methodological approach of observing social reality created through daily actions of scientists. First, Lynch (1985), with his publication ‘art and artifact in laboratory science’, makes clear that science is the result of an ongoing interactional process influenced by certain socially located practices. His insights were deduced from fieldwork within a neuroscience’s la-boratory using participating observation. Second, Latour and Woolgar (1986) with their work ‘laboratory life’, in which they give a fundamental introduction about how to observe scientific work, including the complex embedding of research in an organizational and social network, form a basis for further research.
The contribution of laboratory studies to the field of science and technology studies is significant, because it opened laboratories as a research area for the first time. However, the microscale focus on mostly scientific and abstract methods for the creation of knowledge makes it difficult to apply it to this study. On the one hand, a major difference is given by the focus of analysis. Whereas science is the result of discoveries gained by experiments, technology is the result of design and a concrete production process. Put more simply, technology is the practical transformation of science, which usually materi-alizes as invention. Since care robots are inventions, the focus automatically shifts to the process and interaction between involved actors, which laboratory studies cannot cap-ture adequately.
Latour (1996), Law (1986) and Callon (1986) are considered as the primary developers of the actor-network theory. The actor-network theory gives a theoretical framework for uncovering the interactions of actors and networks accessible for analyzation. According
7 „Neu war, dass sie Naturwissenschaften in der Praxis beobachteten und die lokalen Modalitäten und Pra-xisformen naturwissenschaftlicher Natur- und Wissensproduktion im Labor detailliert beschrieben und ana-lysierten.“ (Amelang 2012, 145)
to this theory, knowledge structures emerge within networks. Laboratory studies, and especially Latour and Woolgar, inspired later research and studies on the actor-network theory. The actor-network theory assumes a strong heterogeneity within networks, which includes humans and non-human beings as actors. Strictly speaking, everything, includ-ing materialized objects as well as abstract thinclud-ings such as institutions, can become a network. Both are equal and active actors, and consequently they have to be treated and analyzed equally. It postulates that “this general symmetry in the analysis makes it pos-sible to uncover that knowledge and technologies are not only defined by social phe-nomena such as hierarchies, interests and values, but also by the contribution of appa-ratus, instruments and other things” 8 (Mathar 2012, 173). In doing so, actor-network the-ory not only attributes the capacity of action to physical objects, but also criticizes SCOT theories through giving material and immaterial objects the possibility of becoming actors.
According to SCOT, humans make technology, but in turn technology influences human action, too. Central for the actor-network theory is that human and non-human actors are equal and organized in networks, where they figuratively work towards a common goal.
In doing so, actor-network theory makes it possible to unveil the relational links within a network, rather than being able to explain why and how a network is constituted as it is.
What is important is the interrelation of several actors within the network. The theory remains very abstract and makes it difficult to build up a theoretical framework for a structured analysis of technology. Nevertheless, actor-network theory sensitizes that it is important to not only take human actors and the emerging invention into account. The outcome is not necessarily in focus, which makes it difficult to apply the theory for anal-ysis onto a specific invention, in this case care robots, as the outcome of a complex process.
At its beginning, feministic STS’ focus was a heterogeneous spectrum covering the in-terrelation between the creation of gender and the development of science. The history of science has mainly been influenced by male researchers and inventors, and left only limited space for women to be mentioned. For this reason, the themes of feministic STS include, for example, the exclusion of women from the history of science, or the prob-lematization of theories, which include social beliefs on gender. Feministic STS experi-enced an upturn in the eighties through the emerging SCOT approach. Early feminists, in particular Harding (1993), urged for a strong objectivism, because scientific objectivity
8 „Diese generelle Symmetrie in der Analyse ermöglicht es sichtbar zu machen, dass Wissen und Techno-logien nicht nur von sozialen Phänomenen, wie Hierarchien, Interessen und Werten definiert werden, son-dern auch durch die Beiträge von Apparaten, Instrumenten und anderen Dingen.“ (Mathar 2012, 173)
and the development of knowledge are subject to social beliefs. Science and technology are the result and manifestation of patriarchal power relations, which can only be over-come by readjusting the specifications of scientific objectivity. In the following years, the progress of biological and medical science questioned the gender- and sex-specific per-ception of the body, and lead to a redefinition of the human as a more or less open and free construct, especially in contrast to a traditional religious understanding. Feministic STS picked up a new understanding of gender, which shifted from its formerly material-orientated focus to paying more attention to the intangible. Feministic STS research and the localized concept of technoscience, which questioned the existing scientific and com-mon practices, are complementary. Donna Haraway (1988, 583) argues that
“The moral is simply: only partial perspective promises objective vision. All Western cultural narratives about objectivity are allegories of the ideologies governing the relations of what we call mind and body, distance and respon-sibility. Feminist objectivity is about limited location and situated knowledge,
“The moral is simply: only partial perspective promises objective vision. All Western cultural narratives about objectivity are allegories of the ideologies governing the relations of what we call mind and body, distance and respon-sibility. Feminist objectivity is about limited location and situated knowledge,