Catching Bugs: The Federal Select Agent Program and Lessons for AI Regulation

AI regulation has made significant strides in recent months. However, any prospective regulator will confront a number of interrelated challenges including: a relative lack of government expertise; an uncertain and rapidly-evolving risk landscape; and the possibility that significant risks may arise during development as well as deployment. We therefore draw lessons from the biosecurity domain, which shares those features to some extent. Specifically, we examine the Federal Select Agent Program (FSAP), the mainstay of the US biosecurity regime. We suggest that FSAP offers both positive lessons for AI regulation, such as providing a precedent for a development-phase licensing regime, and more constructive lessons, relating to the pitfalls of checklist-based regulations as opposed to risk-based regulations.