UC Berkeley

Disruptive technological innovation is the contemporary face of innovation and a dominant force in society. Change is occurring faster and upsetting existing scientific and technical policy systems. Entrepreneurs and innovators, drawing on a folk economic model of regulation, often believe that regulation cannot keep up with the pace of change and therefore policy makers should stay out of their way. Like many folk models, this perception of regulation-as-intrinsic-impediment-to-innovation may sometimes be true but it is not always true. Worse yet, this folk perception of regulators-as-impediment leads entrepreneurs and innovators to ignore opportunities to co-create beneficial regulations and instead create their own bad outcomes by prompting regulators to craft draconian regulations in response to entrepreneurs’ malicious non-compliance.Innovators thus oppose regulation not because they’ve had bad experiences but because they think they will in the future. A popular version of this folk economic model of regulation brandishes the word “disrupt” while storming the halls of stodgy industries and regulatory agencies. Despite this contemporary disruptive innovation narrative, substantial technological change is not a recent invention (though it may be accelerating). The reified economic rhetoric of the folk economic model has convinced disruptive entrepreneurs that regulation is a dirty word synonymous with state inadequacy. Although never perfect and sometimes inadequate, regulators have invariably adapted to technological change. This project explains how regulators have before, are now, and can again become allies of innovators when entrepreneurs look past limiting preconceptions. Regulatory scholars who study actually-existing regulation will recognize the folk economic model as an extreme version of “capture” within “command and control” regulation (c.f. Carpenter and Moss 2014b; Slayton and Clark-Ginsberg 2018). They have repeatedly demonstrated the deceptive inadequacy of totalizing catch-all models of regulation. Nevertheless, scholars who do not study actually-existing regulation often use this folk economic capture baseline to judge all work on regulation which hinders scholarly understanding of relationships between regulation and innovation (c.f. Dal Bó 2006; Carrigan and Coglianese 2015). With these scholarly limitations, lay entrepreneurs’ misperceptions are no surprise. Contrary to the folk model, I argue regulators have been, are now, and can again be so much more than merely a deadweight loss to innovation if only innovators and entrepreneurs can be guided past self-limiting imaginaries such as the folk economic model of disruptive innovation. To develop this argument, I derive a deductive typology of regulatory imaginaries and discuss how we can use this typology to understand the variety of relationships between regulators, entrepreneurs, and innovators that can lead to better or worse effects on innovation. I then specify my novel methodological approach of Bayesian Type Validation (BayesTV) which combines deductive typological theory with logical Bayesian analysis. Finally, I employ BayesTV to inductively verify my typology using three technological cases in the United States and European Union: autonomous vehicles (AVs), gene editing (GE), and electronic health records (EHR). The Folk Economic Model imaginary is but one of seven possible regulatory imaginaries of the proper relationship between regulators, entrepreneurs, and innovators. Regulatory imaginaries, based on the concept of sociotechnical imaginaries (Jasanoff 2015a), are collectively held, publicly performed conceptions of desirable relationships between regulation and technological innovation which actors believe are (or should be) institutionalized within regulatory agencies. Where the Folk Economic Model imaginary sees regulation as only an impediment to be minimized, the other six imaginaries see other potential effects such as moderation, constraint, and catalyst. Critically, my deductively derived and empirically validated typology also demonstrates that regulatory imaginaries are plural, diverse, and malleable. In presenting three empirical chapters covering multiple imaginaries, I demonstrate that there are plural actually-existing imaginaries around well know technologies. In presenting both similarities and differences in the US and EU implementations of regulation for each disruptive technology, I demonstrate that there is meaningful diversity among regulatory imaginaries in conceptual derivation, expected effect on innovation, and empirical implementation. Finally, in the application of BayesTV to the empirical cases, I demonstrate that regulatory imaginaries are malleable through policy. This project focuses on regulatory imaginaries because they shape the perceptions of what is possible and desirable about the relationship between regulators, entrepreneurs, and innovators around disruptive innovation. While future studies should build on this focus on imaginaries by exploring their origins and how contending imaginaries shape the outcomes of the policies that are built around them, this project focuses on the imaginaries themselves in order to demonstrate that we need not limit ourselves to the Folk Economic Model which sees regulation, as a rule, as merely deadweight.