Towards an international regulatory framework for AI safety: lessons from the IAEA’s nuclear safety regulations

Seokki Cha ()
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Seokki Cha: KISTI (Korea Institute of Science and Technology Information)

Palgrave Communications, 2024, vol. 11, issue 1, 1-13

Abstract: Abstract This study explores the necessity and direction of safety regulations for Artificial Intelligence (AI), drawing parallels from the regulatory practices of the International Atomic Energy Agency (IAEA) for nuclear safety. The rapid advancement and global proliferation of AI technologies necessitate the establishment of standardized safety norms to minimize discrepancies between national regulations and enhance the consistency and effectiveness of these rules. The study emphasizes the importance of international collaboration and the engagement of various stakeholders to strengthen the appropriateness of regulations and ensure their continuous updating in response to the evolving risks associated with technological advancements. The paper highlights the critical role of subgoal setting mechanisms in AI’s decision-making processes, underscoring their significance in ensuring the technology’s stability and social acceptability. Improperly tuned subgoal setting mechanisms may lead to outcomes that conflict with human intentions, posing risks to users and society at large. The study draws attention to the hidden risks often embedded within AI’s core decision-making mechanisms and advocates for regulatory approaches to guarantee safe and predictable AI operations. Furthermore, the study acknowledges the limitations of directly applying IAEA’s nuclear safety cases to AI due to the distinct characteristics and risks of the two fields. The paper calls for future research to delve deeper into the need for an independent regulatory framework tailored to AI’s unique features. Additionally, the study emphasizes the importance of accelerating international consensus, developing flexible regulatory models that reflect the situation in each country, exploring harmonization with existing regulations, and researching timely regulatory responses to the fast-paced development of AI technology.

Date: 2024
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DOI: 10.1057/s41599-024-03017-1

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