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Regulation by Benchmark

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 …

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Evaluating AI Systems for Moral Patienthood

Speaker: Rob Long, Center for AI Safety Abstract:  AI systems could plausibly deserve moral consideration in the not-too-distant future. Although precise evaluations are difficult to devise in light of moral and empirical uncertainty about AI moral patienthood, they will be an important tool for handling this issue responsibly and for avoiding both under- and over-attributing …

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