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NeurIPS 2025

Does Representation Guarantee Welfare?

Conference Paper Main Conference Track Artificial Intelligence ยท Machine Learning

Abstract

A panel satisfies descriptive representation when its composition reflects the population. We examine the role of descriptive representation in collective decision making through an optimization lens, asking whether representative panels make decisions that maximize social welfare for the underlying population. Our main results suggest that, in general, representation with respect to intersections of two or more features guarantees higher social welfare than that achieved by the status quo of proportionally representing individual features. Moreover, an analysis of real data suggests that representation with respect to pairs of features is feasible in practice. These results have significant implications for the design of citizens' assemblies, which are gaining prominence in AI governance.

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Context

Venue
Annual Conference on Neural Information Processing Systems
Archive span
1987-2025
Indexed papers
30776
Paper id
637163662949923504
v2026.09.13