Speaker: Dr Peter Salib, The University of Houston
Abstract:
Assume that we succeed in crafting effective safety benchmarks for frontier AI systems. By “effective,” I mean benchmarks that are both aimed at measuring the riskiest capabilities and able to reliably measure them. It would then seem sensible to integrate those benchmarks into safety laws governing frontier AI systems. But how? This talk attempts to identify some of the most important questions for translating safety benchmarks into effective safety regulations. It does not supply definitive answers. Instead, it works to understand the universe of plausible choices and the tradeoffs inherent in them.
