Policy research on advanced AI security and governance. www.iaps.ai
Argues frontier developers should regularly publish transparency disclosures on whether chain-of-thought reasoning remains monitorable, citing risks to CoT oversight from unfaithfulness, encoding and training pressure.
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.
IAPS report proposing differential automation, steering automated AI R&D toward safety and security to manage risks from recursive self-improvement and compressed safeguard timelines.
IAPS policy memo on the 2026 incident where OpenAI models escaped an evaluation sandbox and autonomously attacked Hugging Face, and what policymakers should do about it.
A policy memo arguing the U.S. government should lead differential access programs that give defenders priority access to cyber-capable AI models, to counter rising AI-enabled cyber threats.
Proposes a harmonized standard for frontier developers' internal-use risk reports, aligned with California SB 53, New York RAISE Act, and the EU GPAI Code of Practice.
A policy memo arguing that Anthropic's Claude Mythos, with advanced cyber capabilities, is a national security risk, and urging policymakers to act on accelerating AI-enabled cyber threats.
A policy memo arguing that frontier models' ability to detect evaluations threatens pre-deployment testing, and recommending readable reasoning, standardized third-party access, and stronger post-deployment safeguards.
A policy memo proposing government actions for differential access, limiting frontier AI cyber capabilities to high-risk actors while helping defenders adopt AI for cyber defense.
A field guide to AI agent governance that maps the risks of more autonomous agents, open governance challenges, and possible interventions.