Pro-innovation bias produces epistemic closure- producing innovation as a meta goal obscures structural violence inherent in the process.

(Sebastian M. Pfotenhauer, Munich Center for Technology in Society (MCTS) and TUM School of Management, , Joakim Juhlb Technical University Munich, Germany bDepartment of Planning and Development, Aalborg University, Denmark , Erik AardencDepartment of Science and Technology Studies, University of Vienna, Austria Challenging the “deficit model” of innovation: Framing policy issues under the innovation imperative , Research Policy, https://doi.org/10.1016/j.respol.2018.10.015)

To interrogate the dynamics of a parallel “deficit model of innovation” (DMI), it seems best to take the scholarly investigations into the DMS as a guideline. The starting point is again the question: What kind of deficit is being diagnosed? As has been argued above, the DMI logic intimates that societies are unable to address grand societal challenges or ensure economic competitiveness because their policies, institutions, scientific activities, or individual predispositions are not sufficiently oriented toward innovation – in short, because of a lack of innovation. This lack is usually expressed in terms of innovation capacity, whether at the national, regional, organizational, or individual level. In most cases, the overall diagnosis of a national or regional innovation deficit is immediately accompanied by a range of specific sub-diagnoses about where exactly institutions, policies, or societies are failing to live up to the innovation imperative – whether through a lack of science, technology, engineering, and mathematics (STEM) education, insufficient private sector expenditures on research and development (R&D), riskaverse attitudes, excessive regulation, or inadequate government incentives. For example, in 2015 the Washington Post declared that “Europe’s innovation deficit isn’t disappearing any time soon,” blaming over-regulation and lack of harmonization across the continent (Downes, 2015). The Canadian newspaper The Globe and Mail ran an article titled “Government can’t solve Canada's innovation deficit,” which pointed to a lack of private R&D spending and misguided handpicking of technologies by the government (Yakabuski, 2015). That same year, the Massachusetts Institute of Technology (MIT), in conjunction with the American Association for the Advancement of Science and the Alfred P. Sloan Foundation, released a report “The Future Postponed: Why Declining Investment in Basic Research Threatens a U.S. Innovation Deficit” (MIT, 2015). According to the DMI, these diagnosed deficits require policy action. This action typically takes the form of innovation strategies or initiatives, many of which have been proliferating around the globe (Pfotenhauer and Jasanoff, 2017a). These strategies provide more or less concrete remedies to tackling innovation deficits. For example, the OECD Innovation Strategy (2010) recommends a range of actions, including moving “beyond supply-side policies focused on R&D and specific technologies to a more systemic approach,” adapting “curricula and pedagogies […] to equip students with the capacity to learn and apply new skills throughout their lives,” or making “migration regimes for the highly skilled [more] efficient, transparent and simple and enable movement on a short-term or circular basis.” The report, Innovation Canada: A Call to Action (Jenkins et al., 2011), calls for the government to, among other things, “create an Industrial Research and Innovation Council (IRIC)” or “simplify the scientific research and experimental development (SR&ED) program by basing the tax credit for small and medium-sized enterprises (SMEs) on labour-related costs.” More generally, with its drive toward innovation policy action, the DMI reveals a distinct pro-innovation bias that tends to sideline questions about why social challenges are problems of innovation in the first place or what alternative framings might exist. Likewise, it rarely asks about the broader social consequences of enacting measures such as altering immigration or tax policies in the name of innovation. Like the DMS scientism, it seems “irrational” to oppose initiatives that foster innovation, which appear as the most legitimate way forward. Like PUS, too, the DMI emphasizes the value and critical importance of particular forms of expertise. Innovation itself has grown into a highly technical discourse, rife with its own experts, instruments, and metrics. A growing number of specialized academic journals currently address a broad range of questions and disciplinary perspectives on innovation and have contributed to the emergence of the field of “innovation studies.” Some scholars have pointed to the emergence of a “new disciplinary tribe” of Innovation Studies (Godin, 2014) or traced the emergence of innovation as a distinct form of expertise in the United States (Wisnioski, 2015). International organizations, spearheaded by the OECD, have developed a vast array of comparative innovation indicators, policy manuals, and catalogues of innovation instruments. Successful technology entrepreneurs are widely perceived as authorities on a wide range of public problems that may be solved through innovation, including Peter Thiel, Elon Musk, and Mark Zuckerberg (Pfotenhauer and Juhl, 2017). What is more, a number of regions and institutions – such as Silicon Valley and MIT – have emerged as global reference points for how to be innovative (Pfotenhauer and Jasanoff, 2017b). This emerging expert–lay distinction grants disproportionate power to those who speak on behalf of innovation’s transformative power. In this sense, innovation has ceased to be a purely analytic concept used to explain sociotechnical change and economic growth. Rather, it is a policy goal and a professionalized discourse that is reshaping society in fundamental ways. In particular, the prevalent theorization of innovation as a systemic phenomenon has argued that innovation requires a concerted effort from all other policy domains to flourish. Other policy domains – such as research, education, taxation, immigration, or environmental policy – are increasingly reframed under the DMI, making innovation, in effect, a meta-goal of public policy. To optimize innovation, therefore, innovation policy and its rationales are granted the power to redefine the importance and activities of other social institutions. The DMI restructures social and epistemic orders in yet another way. Decades’ worth of innovation research have emphasized – and perhaps monopolized – the theorization of innovation as a technoeconomic phenomenon (Godin and Lane, 2013; Pfotenhauer and Juhl, 2017). As a result, innovation is seen as desirable not just because of the ways in which technologies enhance our society. Instead, it is equally desirable because it is a major driver of economic growth and hence a key site of global competition (Romer, 1990; Scherer, 1999; Schumpeter, 1934). Electric cars, for example, promise not only cleaner mobility, but also a new car industry that guarantees employment and taxes for generations to come. This dual legitimacy of problem solving and economic prosperity contributes to a situation where innovation can continue to be desirable in economic terms even when the social consequences are questionable or highly disruptive. It is partly through this appeal to competition pressure and a “rising tide lifts all boats” rhetoric of economic growth that makes innovation automatically seem plausible and desirable, and that regularly serves to shortcut political debates about desirability. Both the primacy of economic growth and the policy framing around (national or regional) systems helped establish innovation as an essentially competitive process. Success is measured principally in comparative terms in relation to other nations’ innovation performance. This competition logic is consistent with a broader shift toward benchmarking as a modus operandi in public policy, where progress is typically measured through various “performance gaps.” Benchmarking practices make it possible to present innovation as a matter of “catching up,” “falling behind,” or “staying ahead,” which in turn feeds into “innovation deficits” and “emergencies.” It also resonates with the Darwinist logic of “survival of the fittest” that underwrites evolutionary thinking in innovation theory and concepts such as “disruption” and “creative destruction.” A comparison of deficit logics in PUS and innovation can be found in Table 1.