AI-Relevant Regulatory Precedents: A Systematic Search Across All Federal Agencies

We undertake a systematic search for potential case studies relevant to advanced AI regulation in the United States—the first such case study selection exercise yet conducted.

Relevant case studies that we identify include (among others): the Environmental Protection Agency (EPA); various financial regulators, for example, the Federal Reserve System (“the Fed”) and the Securities and Exchange Commission (SEC); the Office of Commercial Space Transportation (FAA / AST); and regulatory functions within the Department of Energy (DOE) and Department of Defense (DOD).

We identified relevant agencies using quantitative measures of five variables that seem relevant to AI regulation: (1) intensiveness; (2) expertise; (3) enforcement against powerful companies; (4) use of risk-assessments; and (5) focus on / analysis of uncertain phenomena. For variables 1, 4, and 5, we also gathered results at the level of individual regulations.

Note that the intent of this piece is to suggest case studies that researchers or policymakers could examine further. These findings should not be interpreted as endorsements of these regulatory approaches in the context of advanced AI nor as definitive rankings of cases on the five variables.