Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey

• URL: http://arxiv.org/abs/2202.08187v1
• Date: Wed, 16 Feb 2022 16:50:23 GMT
• Title: Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey
• Authors: Ferdinando Fioretto, Cuong Tran, Pascal Van Hentenryck, Keyu Zhu
• Abstract summary: It reviews the conditions under which privacy and fairness may have aligned or contrasting goals. It analyzes how and why DP may exacerbate bias and unfairness in decision problems and learning tasks.
• Score: 50.90773979394264
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper surveys recent work in the intersection of differential privacy (DP) and fairness. It reviews the conditions under which privacy and fairness may have aligned or contrasting goals, analyzes how and why DP may exacerbate bias and unfairness in decision problems and learning tasks, and describes available mitigation measures for the fairness issues arising in DP systems. The survey provides a unified understanding of the main challenges and potential risks arising when deploying privacy-preserving machine-learning or decisions-making tasks under a fairness lens.

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