Abstract

Social choice theory studies the problem of aggregating individual preferences into a single set of preferences for society as a whole. It is typically assumed that one has full access to complete descriptions of each individual's preferences. However, online platforms are emerging which seek to aggregate complex preferences over a vast space of alternatives, rendering it infeasible to learn any individual's preferences completely. Instead, preferences must be elicited by an algorithm using simple queries. In this talk, I will present work from two of my recent papers characterizing both the information-theoretic and computational limits of such algorithms:
https://arxiv.org/abs/2402.11104 - EC 2024 paper about ranked preferences
https://arxiv.org/abs/2211.15608 - AAAI 2023 paper about approval preferences
No prior knowledge of social choice theory will be assumed.

Biography

Jamie Tucker-Foltz is a fifth-year computer science PhD student at Harvard University, advised by Ariel Procaccia. His work is supported by a Google PhD Fellowship and an NSF Graduate Research Fellowship. He earned his undergraduate degree in computer science and mathematics from Amherst College, and a master's degree in computer science from the University of Cambridge on a Churchill Scholarship.

His research focuses on applying techniques from theoretical computer science to improve political and economic institutions. He works on a range of topics in fair division, social choice theory, and algorithmic game theory. He is especially interested in algorithms for fair redistricting and gerrymandering detection. He also has interests in descriptive complexity, computational topology, and graph theory.

See: http://www.jamie.tuckerfoltz.com/

• Admission

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