Regulatory sandboxes for AI in the majority world: A learning-centric approach to legal adaptation

Abstract

Regulatory sandboxes for Artificial Intelligence (AI) are designed to address challenges of rapid technological change. AI innovations create an acute need for learning about what regulation is suitable for enabling innovation while dealing with technological risks. This article argues that regulatory sandboxes should be analyzed primarily as mechanisms for enhancing policymakers’ understanding of technologies such as AI, rather than solely as spaces for experimentation that promote innovation. It discusses the role of regulatory sandboxes in facilitating policy learning that can complement the long-term learning processes of the traditional policy cycle. Six case studies serve to illustrate sandbox elements for enabling collaborative experiential learning in contexts in which the absence of AI regulation makes accelerated policy learning particularly valuable. Looking at the design and governance of regulatory sandboxes from Brazil, Colombia, Mauritius, Mexico, Rwanda, and Thailand, learning elements related to the technology and consequences for closing legal lags emerge as critical components.