Math for AI Safety - Fall 2024 - Lionel Levine - Cornell University - MATH 7710
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AI holds great promise and, many believe, great peril. What can mathematicians contribute to ensuring that promise is fulfilled, and peril avoided? Topics may include: predictive coding, good regulator theorems, Markov decision processes, power-seeking theorems, signaling games, evolution of cooperation, open-source game theory, multi-agent learning, opponent shaping, logical uncertainty, usable information under computational constraints, proper scoring rules, forecast aggregation, Bayesian truth serum, coherence theorems, multi-objective optimization.