Jerrold Soh (Singapore Management U Yong Pung How Law) et al. have posted “Artificial Intelligence in the Regulatory Wonderland” on SSRN. Here is the abstract:
This Chapter conducts a theoretical and practical examination of existing AI governance and regulatory models. With “regulation” we include not only formal legal rules but also soft laws, industry codes, and other regulatory modes. Using existing approaches as case studies, we comment on potential advantages and disadvantages of each model, as well as seek to extract common themes and challenges that accompany AI governance and regulation more generally. Part II sets the theoretical context by scrutinizing two key dimensions implied by the term “AI regulation” itself: (1) “AI” as an object of regulation; and (2) “regulation” itself as a subject of discussion. In Part III, which forms the bulk of this Chapter’s contribution, we visit selected checkpoints along the regulatory spectrum, specifically including self-, co-, quasi-, and direct regulation. Each model will be defined using the regulatory theory literature, exemplified via real world legal instruments, and evaluated by applying the former to the latter. Part IV synthesizes general themes and insights emerging from Part III’s regulatory tour. It identifies how regulatory assessments of the risks and benefits of AI systems appear to differ substantively across jurisdictions. Given the challenges inherent in regulating the use of an opaque, complex, and relatively nascent technology, Part IV further identifies the potential utility of a rigorous AI testing framework.