Why Do AI Regulatory Models Diverge? Risk Perception, Regulatory Choice, and Order Competition in the Age of Generative AI > Journal

Why do major regulatory actors adopt divergent AI regulatory models in response to the same technological shock of generative AI? This article argues that AI regulatory divergence is best understood as a political-economic outcome of risk perception, regulatory choice, and order vision. Departing from the view of AI regulation as an automatic response to objective technological risk, this article conceptualizes it as a deliberate and structured choice made under conditions of uncertainty. It develops a three-dimensional framework centered on regulatory logic, governance structure, and priority value, and applies it to five cases: the United States, the European Union, the United Kingdom, Switzerland, and Finland. The comparison shows that the U.S. model places relatively greater institutional weight on innovation and market dynamism, the European Union emphasizes rights protection and legal accountability, the United Kingdom pursues adaptive pro-innovation governance, Switzerland favors coordinated hybrid regulation, and Finland links AI governance to democratic resilience and social trust. The article further argues that these divergent models are not merely domestic policy variations, but competing visions of technological order. AI regulation increasingly shapes standards, legitimacy, market access, and the balance between innovation and public accountability. The article concludes by discussing implications for South Korea, emphasizing the stabilization and refinement of its emerging layered hybrid regulatory regime.

Introduction

Explaining Divergent AI Regulatory Models: Literature, Framework, and Research Design

Divergent Regulatory Models in the Generative AI Era

Risk Perception, Regulatory Choice, and Order Competition

South Korea's Layered AI Governance and Conclusion

Conclusion

References