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UCL Department of Economics

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Theory/Experimental Seminar - Jay Lu (UCLA)

23 May 2023, 4:30 pm–6:00 pm

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Algorithm Design: a Fairness-Accuracy Frontier" (joint with Annie Liang and Xiaosheng Mu)

Event Information

Open to

All

Organiser

Duarte Goncalves

Abstract: Algorithm designers increasingly optimize not only for accuracy but also fairness, defined as how similar accuracy is across demographic groups. We study the tradeoff between fairness and accuracy via a fairness-accuracy frontier, which consists of the optimal points (for a fixed set of inputs) across a broad range of preferences over fairness and accuracy. Our results identify a simple property of the inputs, group-balance, which qualitatively determines the shape of the frontier. We further study an information-design problem where the designer flexibly regulates the inputs (e.g., by coarsening an input or banning its use) but the algorithm is chosen by another agent. Whether it is optimal to ban an input generally depends on the designer’s preferences. But when inputs are group-balanced, then excluding group identity is strictly suboptimal for all designers, and when the designer has access to group identity, then it is strictly suboptimal to exclude any informative input.

Location: 118 Chandler House or Zoom

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