Mechanisms to Verify International Agreements About AI Development
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Abstract (arXiv)
International agreements about AI development may be required to reduce catastrophic risks from advanced AI systems. However, agreements about such a high-stakes technology must be backed by verification mechanisms--processes or tools that give one party greater confidence that another is following the agreed-upon rules, typically by detecting violations. This report gives an overview of potential verification approaches for three example policy goals, aiming to demonstrate how countries could practically verify claims about each other's AI development and deployment. The focus is on international agreements and state-involved AI development, but these approaches could also be applied to domestic regulation of companies. While many of the ideal solutions for verification are not yet technologically feasible, we emphasize that increased access (e.g., physical inspections of data centers) can often substitute for these technical approaches. Therefore, we remain hopeful that significant political will could enable ambitious international coordination, with strong verification mechanisms, to reduce catastrophic AI risks.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Jun 2025.
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Citing papers per year: 2025: 4; 2026: 5.
9 papers.
- 2026Bit-Exact AI Inference Verification Without Performance Tradeoffscited by 4
- 2025Technical Requirements for Halting Dangerous AI Activitiescited by 2
- 2025Compute Requirements for Algorithmic Innovation in Frontier AI Modelscited by 2
- 2025Against racing to AGI: Cooperation, deterrence, and catastrophic riskscited by 2
- 2025Password-Activated Shutdown Protocols for Misaligned Frontier Agentscited by 0
- 2026International Agreements to Limit Frontier AI: Objectives and Exitcited by 0
- 2026Privacy-Preserving AI Verification via Minimal Information Disclosurecited by 0
- 2026The Closing Window: How Governments Could Lose Their Ability to Restrain Advanced AIcited by 0
- 2026Workload Identification with Physical Side Channels for AI Governancecited by 0
- 2026Workload Identification with Physical Side Channels for AI Governance31 Aug 2026
- 2026Privacy-Preserving AI Verification via Minimal Information Disclosure3 Aug 2026
- 2026The Closing Window: How Governments Could Lose Their Ability to Restrain Advanced AI26 Jun 2026
- 2026International Agreements to Limit Frontier AI: Objectives and Exit19 Jun 2026
- 2026Bit-Exact AI Inference Verification Without Performance Tradeoffs29 May 2026
- 2025Password-Activated Shutdown Protocols for Misaligned Frontier Agents29 Nov 2025
- 2025Against racing to AGI: Cooperation, deterrence, and catastrophic risks29 Jul 2025
- 2025Compute Requirements for Algorithmic Innovation in Frontier AI Models13 Jul 2025
- 2025Technical Requirements for Halting Dangerous AI Activities13 Jul 2025