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arXiv · 2106.08652

Maxmin-Fair Ranking: Individual Fairness under Group-Fairness Constraints

David Garcia-Soriano·Francesco Bonchi
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Abstract

We study a novel problem of fairness in ranking aimed at minimizing the amount of individual unfairness introduced when enforcing group-fairness constraints. Our proposal is rooted in the distributional maxmin fairness theory, which uses randomization to maximize the expected satisfaction of the worst-off individuals. We devise an exact polynomial-time algorithm to find maxmin-fair distributions of general search problems (including, but not limited to, ranking), and show that our algorithm can produce rankings which, while satisfying the given group-fairness constraints, ensure that the maximum possible value is brought to individuals.

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BibTeXRIS

David Garcia-Soriano, Francesco Bonchi. 2021-06-16. Maxmin-Fair Ranking: Individual Fairness under Group-Fairness Constraints. https://arxiv.org/abs/2106.08652

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