Stuart Russell (Computer Science), Lara Buchak and Wesley Holliday (Philosophy), Shachar Kariv (Economics) will co-teach a class on “Foundations for Beneficial AI” during the 2020 Spring Semester.
This interdisciplinary course examines the application of ideas from philosophy and economics to decision making by AI systems on behalf of humans, and in particular to the problem of ensuring that increasingly intelligent AI systems remain beneficial to humans. Solving this problem requires designing AI systems whose objective is to satisfy human preferences while remaining necessarily uncertain as to what those preferences are. The course will study issues arising when applying these principles to make decisions on behalf of multiple humans and real (rather than idealized) humans. Topics include utility theory, bounded rationality, utilitarianism, altruism, interpersonal comparisons of utility, preference learning, plasticity of human preferences, epistemic uncertainty about preferences, decision making under risk, social choice theory, and inequality. Students will read papers from the literature in AI, philosophy, and economics and will work in interdisciplinary teams to develop substantial analyses in one or more of these areas. No advanced mathematical background is assumed, but students should be comfortable with formal arguments involving axioms and proofs.