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In this 1-hour 5-minute lecture from the Simons Institute for the Theory of Computing and SLMath Joint Workshop on AI for Mathematics and Theoretical Computer Science, Emily Riehl from Johns Hopkins University explores methods for evaluating artificial intelligence systems in mathematical contexts. Drawing inspiration from Thurston's essay "On proof and progress in mathematics" and Turing's "Computing machinery and intelligence," discover a proposed series of tests designed to assess whether generative AI systems can meaningfully contribute to mathematical processes. Learn about the multifaceted nature of mathematical accomplishment and how these evaluation frameworks might help determine the potential role of AI in advancing mathematical knowledge.
