IAPS Researchers React: The US AI Action Plan
The Trump Administration unveiled its comprehensive AI Action Plan on Wednesday. Experts at the Institute for AI Policy and Strategy reviewed the plan with an eye toward its national security implications. As AI continues to accelerate towards very powerful artificial general intelligence, our researchers discuss promising proposals for addressing critical AGI risks, offer key considerations for government implementation, and explore the plan's gaps and potential solutions.
The US Government’s Role in Advanced AI Development: Predictions and Scenarios
There has been significant recent speculation about whether the US government will lead a future project to build and acquire advanced AI, or continue to play a more arms-length role. We conducted a forecasting workshop on this question, employing the IDEA protocol to elicit predictions from six professional forecasters and five experts on US AI policy.
Response to the DOD RFI on Defense Industrial Base Adoption of Artificial Intelligence for Defense Applications
IAPS submitted a response to a Department of Defense Request for Information on Defense Industrial Base Adoption of AI for Defense Applications.
AI-Relevant Regulatory Precedents: A Systematic Search Across All Federal Agencies
A systematic search for potential case studies relevant to advanced AI regulation in the United States, looking at all federal agencies for factors such as level of expertise, use of risk assessment, and analysis of uncertain phenomena.
Responsible Scaling: Comparing Government Guidance and Company Policy
This issue brief evaluates the original example of a Responsible Scaling Policy (RSP) – that of Anthropic – against guidance on responsible capability scaling from the UK Department for Science, Innovation and Technology (DSIT).
Catching Bugs: The Federal Select Agent Program and Lessons for AI Regulation
This paper examines the Federal Select Agent Program, the linchpin of US biosecurity regulations. It then draws out lessons for AI regulation regarding licensing, regulatory expertise, and the merits of “risk-based” vs. “list-based” systems.