In Silico Comparative Competition Law (INSICOL)

This collaborative research project pioneers a novel methodology in comparative legal studies: in silico legal comparison. By integrating insights from empirical comparative law and experimental legal studies, it advances an emerging field that leverages Large Language Models (LLMs) for comparative institutional and legal analysis. The field of competition law is particularly fruitful for such research, in view of the different substantive law approaches followed in each jurisdiction, the variety of institutional designs and the commonality of the competition problems and business conducts examined, given the global strategies of digital market players and the influence of economic analysis in competition law. The research will make the following three contributions:
First, the research examines how and why the United States (US), the United Kingdom (UK), and the European Union (EU) differ in their regulatory responses to addressing competitive risks generated by AI technologies and digital ecosystems in their respective markets. It maps institutional frameworks and substantive rules across these three jurisdictions, identifying key differences in regulatory/antitrust approaches. It then employs AI simulation tools to model how businesses respond to the different components of these regulatory environments. By testing different scenarios using vignettes, we examine how competition law enforcement and digital competition regulation can address competitive risks related to AI and digital ecosystems. These simulations reveal how tech companies can adapt their strategies in response to regulatory pressure and how consumers and other stakeholders may react to them. We demonstrate precisely which regulatory designs are likely to be effective in specific legal contexts - and which might backfire. The research thus comprehensively examines the institutional frameworks and substantive regulations governing AI- and digital ecosystem-related competition risks, illuminating...