论文标题
决策和学习任务中的差异隐私和公平性：一项调查
Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey
论文作者
论文摘要
本文调查了差异隐私（DP）与公平性交集中的最新工作。它审查了隐私和公平性可能使目标保持一致或对比目标的条件，分析了DP如何以及为什么会加剧决策问题和学习任务的偏见和不公平性，并描述了DP系统中出现的公平问题的可用缓解措施。该调查提供了对在公平镜头下部署隐私的机器学习或决策任务时，对主要挑战和潜在风险的统一理解。
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.
