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Talk Information:
When Monday Oct 21st 1:00pm
Where: HDSI MPR 123
Zoom Info: http://bit.ly/HDSI-Seminars
Title: Generative Social Choice
Abstract: “The mathematical study of voting, social choice theory, has traditionally only been applicable to choices among a few predetermined alternatives, but not to open-ended decisions such as collectively selecting a textual statement. This limitation is addressed by generative social choice, a design methodology for open-ended democratic processes that combines the rigor of social choice theory with the capability of large language models to generate text and extrapolate preferences. I’ll introduce a framework that divides the design of AI-augmented democratic processes into two components: first, proving that the process satisfies representation guarantees when given access to oracle queries; second, empirically validating that these queries can be approximately implemented using a large language model. I’ll also discuss the application of this framework to the problem of summarizing free-form opinions into a proportionally representative slate of opinion statements. By providing rigorous guarantees, generative social choice could alleviate concerns about AI-driven democratic innovation and help unlock its potential.
Bio: Ariel Procaccia is Gordon McKay Professor of Computer Science at Harvard University. He works on a broad and dynamic set of problems related to AI, algorithms, economics, and society. He has helped create systems and platforms that are widely used to solve everyday fair division problems, resettle refugees and select citizens’ assemblies. To make his research accessible to the public, he regularly writes opinion and exposition pieces for publications such as the Washington Post, Bloomberg, Wired and Scientific American. He is a AAAI Fellow (2024) and a recipient of the ACM SIGecom Mid-Career Award (2024), Social Choice and Welfare Prize (2020), Guggenheim Fellowship (2018), IJCAI Computers and Thought Award (2015) and Sloan Research Fellowship (2015).