Fairness-Utility Trade-off via Wasserstein Projection

• URL: http://arxiv.org/abs/2505.11678v1
• Date: Fri, 16 May 2025 20:29:06 GMT
• Title: Fairness-Utility Trade-off via Wasserstein Projection
• Authors: Yan Chen, Zheng Tan, Jose Blanchet, Hanzhang Qin,
• Abstract summary: We propose a fairness framework that enforces strong demographic parity-related fairness criteria while guaranteeing a minimum total utility.<n>This approach balances equity and utility by calibrating propensity scores to satisfy fairness criteria and optimize outcomes without incurring unacceptable losses in performance.
• Score: 3.219357970804902
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Ensuring fairness in data-driven decision-making is a critical concern, but existing fairness constraints often involve trade-offs with overall utility. We propose a fairness framework that enforces strong demographic parity-related fairness criteria (with $\epsilon$-tolerance) in propensity score allocation while guaranteeing a minimum total utility. This approach balances equity and utility by calibrating propensity scores to satisfy fairness criteria and optimizing outcomes without incurring unacceptable losses in performance. Grounded in a binary treatment and sensitive attribute setting under causal fairness setup, our method provides a principled mechanism to address fairness while transparently managing associated economic and social costs, offering a practical approach for designing equitable policies in diverse decision-making contexts. Building on this, we provide theoretical guarantee for our proposed utility-constrained fairness evaluation framework, and we formalize a hypothesis testing framework to help practitioners assess whether the desired fairness-utility trade-off is achieved.

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