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Abstract This paper delves into the complexities of global AI regulation and governance, emphasizing the socio-economic repercussions of rapid AI development. It scrutinizes the challenges in creating effective governance structures amidst the AI race, considering diverse global perspectives and policies. The discourse moves beyond specific corporate examples, addressing broader implications and sector-wide impacts of AI on employment, truth discernment, and democratic stability. The analysis focuses on contrasting regulatory approaches across key regions—the United States, European Union, Asia, Africa, and the Americas and thus highlighting the variations and commonalities in strategies and implementations. This comparative study reveals the intricacies and hurdles in formulating a cohesive global policy for AI regulation. Central to the paper is the examination of the dynamic between rapid AI innovation and the slower pace of regulatory and ethical standard-setting. It critically evaluates the advantages and drawbacks of shifting regulatory responsibilities between government bodies and the private sector. In response to these challenges, the discussion proposes an innovative and integrated regulatory model. The model advocates for a collaborative network that blends governmental authority with industry expertise, aiming to establish adaptive, responsive regulations (called “dynamic laws”) that can evolve with technological advancements. The novel approach aims to bridge the gap between rapid AI advancements in the industry and the essential democratic processes of law-making.
Yoshija Walter (Mon,) studied this question.