The development of frontier AI models has exposed critical gaps in existing risk management approaches. While AI companies have initiated safety protocols, they often lack the systematic rigor found in other high-risk fields. This paper underscores the pressing need for a more structured and transparent risk management process, particularly in light of increasing concerns over AI misuse, model failures, and regulatory shortcomings. The authors emphasize that AI risk management should not be an afterthought; rather, it must be embedded into every stage of AI development, from conceptualization to deployment.
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