Reducing Leximin Fairness to Utilitarian Optimization

Research output: Contribution to journalConference articlepeer-review

Abstract

Two prominent objectives in social choice are utilitarian - maximizing the sum of agents’ utilities, and leximin - maximizing the smallest agent’s utility, then the second-smallest, etc. Utilitarianism is typically computationally easier to attain but is generally viewed as less fair. This paper presents a general reduction scheme that, given a utilitarian solver, produces a distribution over states (deterministic outcomes) that is leximin in expectation. Importantly, the scheme is robust in the sense that, given an approximate utilitarian solver, it produces a lottery that is approximately-leximin (in expectation) - with the same approximation factor. We apply our scheme to several social choice problems: stochastic allocations of indivisible goods, giveaway lotteries, and fair lotteries for participatory budgeting.

Original languageEnglish
Pages (from-to)13905-13914
Number of pages10
JournalProceedings of the AAAI Conference on Artificial Intelligence
Volume39
Issue number13
DOIs
StatePublished - 11 Apr 2025
Event39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025 - Philadelphia, United States
Duration: 25 Feb 20254 Mar 2025

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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