Bare Minimum Mitigations for Autonomous AI Development

Joshua Clymer; Isabella Duan; Chris Cundy; Yawen Duan; Fynn Heide; Chaochao Lu; Sören Mindermann; Conor McGurk; Xudong Pan; Saad Siddiqui; Jingren Wang; Min Yang; Xianyuan Zhan

arXiv · 2504.15416

Bare Minimum Mitigations for Autonomous AI Development

Joshua Clymer·Isabella Duan·Chris Cundy·Yawen Duan·Fynn Heide·Chaochao Lu·Sören Mindermann·Conor McGurk·Xudong Pan·Saad Siddiqui·Jingren Wang·Min Yang·Xianyuan Zhan

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Abstract

Artificial intelligence (AI) is advancing rapidly, with the potential for significantly automating AI research and development itself in the near future. In 2024, international scientists, including Turing Award recipients, warned of risks from autonomous AI research and development (R&D), suggesting a red line such that no AI system should be able to improve itself or other AI systems without explicit human approval and assistance. However, the criteria for meaningful human approval remain unclear, and there is limited analysis on the specific risks of autonomous AI R&D, how they arise, and how to mitigate them. In this brief paper, we outline how these risks may emerge and propose four minimum safeguard recommendations applicable when AI agents significantly automate or accelerate AI development.

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Joshua Clymer, Isabella Duan, Chris Cundy, Yawen Duan, Fynn Heide, Chaochao Lu, Sören Mindermann, Conor McGurk, Xudong Pan, Saad Siddiqui, Jingren Wang, Min Yang, Xianyuan Zhan. 2025-04-21. Bare Minimum Mitigations for Autonomous AI Development. https://arxiv.org/abs/2504.15416

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