Techno-economic Assumptions

Introduction

Contemporary capitalism is increasingly technoscientific. Examples of this include the growing role of techno-economic expertise in decision-making, such as economists specializing in research and innovation policy; the social dominance of techno-economic knowledge claims, such as the quality of life benefits of pharmaceutical products; the financial importance of technoscientific organizational structures and governance, such as the ‘unicorns’—that is, companies valued at US$1 billion plus, despite never producing a thing or a profit—rearing their heads across Silicon Valley; and the continuing transformation of social institutions into producers of technoscientific outputs, such as universities and the ‘epistemic rentiership’ engendered by academic publishing processes (Harvie et al., 2014; Fuller, 2016). At the same time, a growing techno-economic optimism inflects popular and political imaginaries around the relationship between capitalism and technoscience, representing the latter as the solution to problems with and crises in the former (Morozov, 2013; Keen, 2015).

Economic assumptions underpin all of this, especially the enormous range of ‘expert’ and ‘lay’ judgements regarding the value and purpose of technoscience. Such assumptions frequently remain implicit, however, meaning that they are unaccountable, despite the powerful influence they have on an array of decisions, policies, media representations, public engagements, professional claims, and so on. Examples of these assumptions are rife, and I can only offer a few here. Standards of living and livelihoods are frequently equated with rising GDP; human behavior and decision-making are frequently related to naturalized notions of competitive individualism; government policies are frequently assessed against conceptions of efficiency based on financial cost-benefit analysis; capital-intensive technologies are frequently normalized as innovation, and, in contrast, their opposites are denigrated as stagnation; technology is frequently promised as the solution to societal challenges, as well as the fount of financial returns; and successful product development is frequently assumed to follow public acceptance (Muniesa, 2014; Roy and King, 2016; Birch, 2017). For all such issues, the underlying assumptions are normative and constitutive, even if claiming to be merely descriptive.

As Welsh and Wynne (2013) note, however, there is a growing resistance to these sorts of economic assumptions and their embedding of a particular attitude to technoscience, namely as an unambiguous driver or source of ‘national economic progress’ (see Hess, 2010; de Saille, 2015; de Saille and Medvecky, 2016). Given that technoscience and economics are increasingly entangled as ontological and epistemic objects, as knowledges and as practices, more work is necessary to unpack the economic assumptions underpinning technoscience. The emergence and ascendancy of technoscientific capitalism, as Sunder Rajan (2006) and others call it (e.g. Lyotard, 1984), represents a critical moment for science and technology studies (STS) to engage with this task. In light of these concerns, it makes conceptual and normative sense for STS scholars to analyze economic assumptions, and to unpack the economic black boxes that are often left unopened when we dig into the other assumptions underlying technoscience (Wynne, 1988). Obviously, this raises numerous questions and opportunities for STS scholars, but the key questions would be: How might STS scholars conceptualize the economic assumptions implicit in technoscience? And, in what ways are the logics, practices, subjectivities, and actors that constitute economic assumptions and technoscience increasingly blurred?

This special forum seeks to address these questions and illustrate how STS scholars might engage further with such topics through an analysis of economic assumptions and their roles in science, technology, innovation, and expertise.

Economic concepts in STS

An obvious starting point is to ask, what is an ‘economic assumption’? Rather than turn to the dictionary for an answer, it is more helpful—analytically and normatively speaking—to review the STS literature on economic ideas and their constitutive effects. Relevant STS literature can be classified into three broad camps, although there are other possible ways to frame this discussion.¹

Performative roles

First, there has been a significant engagement with economics and finance from an STS perspective, especially how economic ideas play a performative role in shaping or configuring the ‘economy’. Two decades ago Callon (1998) edited a key volume contributing to these debates, called Laws of the Markets, in which he posited a theory of economics ‘performativity’. Simply put, he argued that economic theories are not descriptive, but rather performative: economists’ theories, ideas, and assumptions constitute the very economy they seek to theorize or explain. As such, economists and others constitute the economy through their discursive actions.

Subsequently, other STS scholars adapted performativity in their own ways. MacKenzie (2006) explored different forms of performativity, while Muniesa (2014) analyzed how the economy is ‘provoked’ through a series of everyday ‘practical tests’. These engagements with economics turn an STS gaze onto specific and particular forms of economic expertise, knowledge, and claim-making, without resorting to normative critiques of economics as ‘missing the point’ or not understanding the implications of social structure. Rather, this literature has engaged with economic assumptions on the terms set out by economists, and thereby highlighted how the economy can be conceived as performatively constituted by the economic ideas or assumptions of economists.

Political economy of technoscience

Second, and perhaps at odds with the first group above, there has been a growing interest in STS circles in examining the changing political economy of research and innovation (see Birch, 2013; Tyfield et al., 2017), especially as this relates to the influence of particular political-economic regimes (e.g. neoliberalism). Examples here include STS scholars like Mirowski (2004, 2011) and Tyfield (2012, 2018) who both stress the need to examine the transformation of technoscience engendered by processes of commercialization, commodification, and corporatization that followed from broader societal changes, rather than reflecting particular actor- or network-level assemblages. As Mirowski (2004, pp. 311–312, p. 315) puts it, ‘something rather dramatic has happened to the organization of science and the university in the quarter-century or so since 1980’, which is characterized by ‘a corporate dominance over the practice of science’.

In some ways, this engagement with economics—or, more specifically, political economy—reverses the order of play of the performativity approach; that is, it seeks to understand how (political-)economic assumptions (e.g. markets are the best way to organize scientific research) configure technoscience, although not necessarily in a performative manner (e.g. there can be significant unintended or unforeseen consequences), rather than how economics, and its technoscientific apparatus, constitutes the economy. STS and cognate disciplines have engaged with these issues for some time, notably in the work of Hackett (1990, 2014) and Slaughter and Rhoades (2004) on ‘academic capitalism’. Going further, some scholars like Mirowski and Tyfield link the political and economic aspects, often missing from STS literature. They highlight the continuing co-construction of technoscience and capitalism, drawing attention to the effects neoliberalism on research and innovation (e.g. Lave et al., 2010; Pellizzoni and Ylönen, 2012; Tyfield et al., 2017; Birch et al., forthcoming).

Technological expectations

Finally, and perhaps most relevant to the focus of this special forum, is the work of STS scholars on the ‘sociology of technological expectations’, or STEs (e.g. van Lente, 1993; Brown et al., 2000; Brown and Michael, 2003; Borup et al., 2006; Selin, 2008). As should be evident from the tagline, the STE literature emphasizes the constitutive role of expectations on technoscience, specifically future expectations. According to Brown and Michael (2003, p. 7), for example, there is a need to study ‘how the future is mobilized in real time to marshal resources, coordinate activities and manage uncertainty’. From this perspective, expectations are ‘generative’ in that they provide direction, legitimation, and create interest in technoscientific solutions, bridging the temporal distance between current research agendas and future research outcomes.

As early exponents of this approach note (e.g. van Lente and Rip, 1998), such expectations are particularly important for so-called enabling technologies, such as information technology, biotechnology, and nanotechnology. Furthermore, Brown et al. (2000) make the point that these sorts of enabling technology are dependent on enrolling public and private resources and are often then celebrated as ‘breakthroughs’, despite lacking accountability for the promised expectations. Consequently, Brown and Michael (2003, p. 13) point out that:

… the basic dynamics of the futures market means that expectations are capable of generating enormous near-term share value (with which to conduct research or financially reward research staff), but without any necessary requirement for entrepreneurs to fulfil their longer-term promises.

A considerable literature has built up around this research agenda, including topics such as animal biotechnology (Valiverronen, 2004), pharmacogenomics (Hedgecoe and Martin, 2003), xenotransplantation (Brown, 2003), bioenergy (Levidow et al., 2013), etc. Colleagues and I have sought to extend this research agenda to the institutional context of technoscience through our studies of policy frameworks in European Union research and innovation policy-making (e.g. Levidow et al., 2012; Birch et al., 2014), while others, in related fields like economic sociology, have sought to theorize ‘fictional expectations’ as ‘motivating forces’ for economic action (Beckert, 2011). More recently, scholars like Coleman and Tutton (2017) stress the relevance of ‘futures’ research across the social sciences.

As with other STS literatures, those developing the STE focus are concerned with how certain ‘assumptions’—or, more specifically, expectations in their terminology—help mobilize resources in the pursuit of technoscience. However, rather than representing an example of discursive performativity or political-economic regime, the STE literature argues that future expectations are constitutive because of their role in ‘in brokering relationships between different actors and groups’ (Borup et al., 2006, p. 289). In and of themselves, expectations need not be generative of those social relations, but rather they bring together diverse groups.

Towards an interdisciplinary critique of techno-economic assumptions

I now want to return to ‘economic assumptions’ after this diversion through STS debates, and suggest that there is a likewise need for a sociology of techno-economic assumptions, as there is for a sociology of technological expectations (see above). I put ‘sociology’ in scare quotes to emphasize that this need not be a sociological analysis alone, it could—and should—be an interdisciplinary project bringing together sociology, anthropology, geography, political science, law, and other social sciences in the analysis of techno-economic assumptions. Moreover, I have added ‘techno-’ as a prefix to ‘economic’ to stress the need for STS scholars to analyze the technoscientific and economic configuration of our societies.

Analytically, it is important to take a dual approach in unpacking techno-economic assumptions. On the one hand, it is necessary to analyze claims making, or the production of knowledge; on the other hand, it is necessary to analyze the staking of claims, or the assertion of expertise. First, assumptions are underpinned by making claims about what is and what is not knowledge (Beamish, 2007; Beckert, 2011), which tends to refer to past framings or visions of the world. This contrasts somewhat with the STE approach discussed above, which is more concerned analytically with the future. For example, techno-economic assumptions about the proper role and purpose of science in policy circles remain wedded to the longstanding idea that there is a linear model of innovation (e.g. HM Treasury, 2014), despite its intellectual paucity (Godin, 2006). The ongoing adherence to this assumption, in the face of counter-knowledges about diverse innovation models—see, for example, Oudshoorn and Pinch (2003) on user innovation—illustrates the ongoing narrative strength of past ‘knowledge’ claims.

Second, assumptions entail staking a claim as to the proper and professional methods of knowledge production as well. Again, this reflects a focus on the past, although in this case on the past achievements of the claims makers; namely, whether they have the right credentials to be making proper—descriptively and normatively—knowledge claims. Fuller (2016) identifies this staking of claims in the social conditions of knowledge production as ‘epistemic rent-seeking’. For example, academic researchers have to reference the ‘correct’ literature when trying to publish their own research or they will face possible rejection by journal gatekeepers (e.g. referees, editors). As such, this creates barriers to entry to knowledge production, ranging from resource issues (e.g. institutional access to academic journals) to the professional coercion of junior researchers by their more senior colleagues (e.g. being forced to cite supervisors or managers).

Relevance to STS

As the above discussion and the contributions to this special forum illustrate, techno-economic assumptions have constitutive effects. These need not be performative—that is, reflect the underlying discursive claim. Instead, they could well prove ‘counter-performative’ (MacKenzie, 2006). Next, I introduce the relevance of this analysis of techno-economic assumptions to STS and introduce the various contributions to the special forum.

First, at a general level techno-economic assumptions provide the basis for understanding the world. In turn, these understandings are generative or constitutive of the world, in that the belief in a particular claim provides the basis for decisions, rather than the actual contents of the claim itself (see Beckert, 2011). For example, finance, financial markets, and financial governance entail a specific understanding of the world that shapes the normative framing of decisions, outcomes, and processes. Chiapello (2015) argues that financial assumptions have infiltrated other ways of understanding the social world, especially through concepts like ‘opportunity cost’—that is, the highest potential alternative value of any monetary expenditure. These financial assumptions frame our understanding of whether something is worthwhile or not, on the basis of specific valuation judgements (e.g. discounting future revenues in the present—see Muniesa, 2012).

As a result, certain understandings of the world become almost incomprehensible when they are not judged on the basis of the value they ‘create’—this is discussed in Muniesa’s (2017) article in this special forum. Here, Muniesa argues that notions like ‘value creation’ help to constitute a variety of social actors as ‘investors’, rather than citizens or publics or protestors, and innovation as an investment rather than collective political decision or choice. Similarly, in her article on drug pricing in the pharmaceutical industry, Glabau (2017) argues that ‘price in the pharmaceutical industry today is a highly orchestrated accomplishment with no natural referent’. In both cases, it does not matter whether the content of the assumption is ‘correct’, since a belief in the assumption provides the means to decide and take action. A final example in the special forum is Helgesson and Lee’s (2017) article on adaptive drug trials; they show how ‘competition’ ends up shaping different notions of valuation in both traditional (e.g. comparing two or more drug candidates) and adaptive (e.g. pursuing only one drug candidate in development) clinical trial designs.

Second, techno-economic assumptions configure the political-economic conditions of research funding, research organizational structure, research governance, and research policies. As Tyfield (2012) points out, the funding of research and innovation matters because it shapes the way said research and innovation can and does happen; for example, in a university setting, or in a corporate setting. Assumptions underpin the organizational setting as well as the governance of that setting and of research endeavors (Kleinman and Vallas, 2001). An example is the shift in the USA engendered by the 1980 Bayh-Dole Act, which transferred intellectual property rights from federally-funded research to universities (and subsequently businesses). The assumption that universities were and are best placed to facilitate innovation led to the proliferation of technology transfer offices across American universities after this change, as well as increasing limits on sharing research materials across research units and universities (Mirowski, 2011). Whether or not this has facilitated technology transfer—with some arguing that it has not (Geiger and Sa, 2009)—becomes a moot point.

Returning to Glabaus’s (2017) article, she argues that assumptions about shareholder maximization, embedded in the organization and governance of the public corporation, ‘has reconfigured how pharmaceutical companies make drugs and generate new streams of income’. Similarly, Helgesson and Lee (2017) argue that different clinical trial designs configure the knowledge that gets produced, in that adaptive drug trials create far less knowledge about drug candidates that do not get chosen. Along a slightly different track, Cañibano (2017) unpacks the neoclassical assumption, inspired by human capital theory, that scientific mobility necessarily entails a zero-sum loss or gain as scientists move from one country to another. From this perspective, scientists are seen as valuable labor inputs in the economic system, but Cañibano argues that the networked organization and structure of technoscientific knowledge means that it is better to think of scientific mobility as reconfiguring ‘research networks by altering the structure of complementarities in both the sending and the recipient networks’. Consequently, scientific mobility generates a range of new possibilities, networks, and knowledge that is not simply embodied in the individual scientist.

Third, techno-economic assumptions limit the potential pathways for change and transformation by closing down the alternatives that an individual or social group can choose from, akin to the analysis of future expectations (Borup et al., 2006). It is increasingly evident, for example, that techno-economic assumptions limit the scope for citizen engagement in deciding upon the aims or effects of technoscience or capitalism, outwith a very narrow framework in which publics are confined to specific roles (Welsh and Wynne, 2013; de Saille, 2015). In their articles for this special forum, both Scoville (2017) and Beumer (2017) show how certain assumptions close down certain decisions as possible choices. First, Scoville argues that assumptions about economic ‘efficiency’ push environmental sciences to finding the ‘optimal’ solution to ecological problems. Optimal is framed as the sweet spot between economic and environmental considerations, such that other, non-economical, solutions are derided as impractical. Second, Beumer argues that the governance of nanotechnology in South Africa has framed publics as consumers of new products, rather than as citizens concerned about social, health, or environmental risks. As a result, this limits the potential of citizens to engage with nanotechnology beyond their consumption behavior.

Fourth, the ascendance of technoscientific capitalism—by which I mean the increasing co-production of capitalism and technoscience—means that techno-economic assumptions are likely to become more influential over time (Lyotard, 1984; Sunder Rajan, 2006). Increasing complexity necessarily entails the increasing deployment of expertise, whether scientific or policy or otherwise. From one perspective, there is a risk that these assumptions will become increasingly implicit, unaccountable, and uncontested or uncontestable as a result (de Saille, 2015). However, complexity also opens up opportunities for challenges to assumptions, as a result of the contradictions between assumptions and/or in claims about expertise.

As technoscience reconfigures capitalism, and vice versa, the assumptions that underpin techno-economic expertise necessarily multiply, covering a broader array of decisions, choices, and policies, and making it more difficult to create consensus amongst experts and publics. The first example of this process in this special forum is Birkbak’s (2017) article on the implementation of a congestion charge in Copenhagen, Denmark. While this congestion charge was framed by assumptions from neoclassical economics, its eventual sociotechnical collapse resulted from the fact that it, like many other policies, was comprised of (contested) benefits and disadvantages for different social groups. The second example is Fuchs and Schalljo’s (2017) analysis of the way German business managers are challenged by the takeover of German firms by their Chinese, Russian, and Indian equivalents. Here Fuchs and Schalljo show how German managers expect their new owners to adapt to their way of thinking leading to forms of ‘othering’ as a way to cement their own assumptions. Generally, the proliferation of assumptions can threaten societal action as it becomes nearly impossible to bring together different social groups with different goals and interests; as a result, these difficulties can generate suspicion of expertise and experts.

Further issues

Several questions or issues are left unanswered or unaddressed in this special forum. Of critical importance to STS is an examination of our own assumptions, especially with regard to the influence of economic ideas in our core concepts; for example, assumptions about individual rational and market actors are implicated in actor-network theory and organizational network analyses (Birch et al., forthcoming). Another critical issue for STS is understanding how assumptions are kept implicit, how they are made explicit, and how they can be actively contested; this means unpacking the normative stances regarding capitalism and technoscience of other experts and of ourselves, perhaps as the starting point for a rehabilitation of political-economic processes, practices, and devices (e.g. markets or instruments creating them). Obviously, all this means STS needs to engage with new objects and subjects of research, primarily with economics and economists; this means developing new competencies in areas like economics, finance, political economy, and suchlike. Finally, it is critical that we work out how our efforts can challenge different forms of economic expertise and understand what these forms might be replaced with—e.g. democratic, ecological, and/or affective values.

Acknowledgements

Special thanks to Les Levidow for his editorial advice, encouragement, and insight during the process of putting this special forum together.

Disclosure statement

No potential conflict of interest was reported by the authors.

Note on contributor

Kean Birch wrote this guest introduction while he was a Visiting Scholar in the Department of Business and Politics at Copenhagen Business School, Denmark. He is also a Senior Associate at the Innovation Policy Lab, University of Toronto, Canada and an Associate Professor in the Department of Geography, York University, Canada. His recent books include We Have Never Been Neoliberal (2015, Zer0 Books), Innovation, Regional Development, and the Life Sciences: Beyond Clusters (2016, Routledge), Business and Society: A Critical Introduction (2017, Zed books—with Mark Peacock, Richard Wellen, Caroline Hossein, Sonya Scott, and Alberto Salazar), and A Research Agenda for Neoliberalism (2017, Edward Elgar). He is also co-editor, with Simon Springer and Julie MacLeavy, of The Handbook of Neoliberalism (2016, Routledge).

Notes

1 One example is the work of STS and other scholars on the materialities of economic actors, objects, and understandings of the world (e.g. Mitchell 2011; Sunder Rajan 2012; Collard and Dempsey 2013). This research agenda has, in particular, built up around academic journals like The Journal of Cultural Economy.