Policy research on advanced AI security and governance. www.iaps.ai
Argues that contract terms will determine whether embedded third-party evaluators at frontier AI companies provide a real safety check, and calls for credible agreements now.
A policy memo proposing a national CAISI+ center in the US Commerce Department for frontier model evaluations of catastrophic risks, emergency assessment, and AI security research, with budget and infrastructure recommendations.
IAPS's response to a US federal RFI recommends AI R&D priorities on model security, reliability and capability assessments, supply chain security, and monitoring adversary AI, citing misalignment risks.
A blog post on an Oxford Martin AI Governance Initiative paper examining which actors, such as governments, labs or third parties, should develop which AI model evaluations.
A governance primer analysing the first wave of AI Safety Institutes (UK, US, Japan), comparing their shared characteristics, core functions of research, standards and cooperation, and challenges.
A policy memo proposing Congress create an early warning system for novel AI-enabled threats, with BIS as a clearinghouse for dual-use capability evaluation reports from frontier developers.
Proposes a Coordinated Disclosure of Dual-Use Capabilities process, with a government clearinghouse receiving reports of dangerous AI capabilities so defenders get early warning and time to respond.
IAPS's response to NIST recommends that external actors get access and resources for scrutiny of dual-use foundation models, with incident response plans for dangerous capabilities and defense-in-depth.