Generative Social Choice

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. We introduce 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. Our framework 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. We apply this framework to the problem of summarizing free-form opinions into a proportionally representative slate of opinion statements; specifically, we develop a democratic process with representation guarantees and use this process to represent the opinions of participants in a survey about chatbot personalization. In a trial with 100 representative US residents, we find that 93 out of 100 participants feel “mostly” or “perfectly” represented by the slate of five statements we extracted. By providing rigorous guarantees through social choice, our work alleviates concerns about AI-driven democratic innovation and helps unlock its potential.

Bio: Paul Gölz is currently a postdoc at UC Berkeley and will start as an assistant professor at Cornell ORIE in Summer 2024. Before that, he was the Sloan Foundation supported postdoctoral fellow of the Algorithms, Fairness, and Equity program at the Simons Laufer Mathematical Sciences Institute (formerly: MSRI), a postdoctoral fellow at Harvard, and received his Ph.D. in computer science at Carnegie Mellon University. Paul studies democratic decision making and the fair allocation of resources, using tools from algorithms, optimization, and artificial intelligence. Algorithms developed in his work are now deployed to select citizens’ assemblies around the world and to allocate refugees for a major US resettlement agency.