{"type":"ScholarlyArticle","title":"Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey","authors":[{"name":"Ferdinando Fioretto","slug":"ferdinando-fioretto","given":"Ferdinando","family":"Fioretto","affiliation":"Syracuse University"},{"name":"Cuong Tran","slug":"cuong-tran","given":"Cuong","family":"Tran","affiliation":"Syracuse University"},{"name":"Pascal Van Hentenryck","slug":"pascal-van-hentenryck","given":"Pascal","family":"Van Hentenryck","affiliation":"Georgia Institute of Technology"},{"name":"Keyu Zhu","slug":"keyu-zhu","given":"Keyu","family":"Zhu","affiliation":"Georgia Institute of Technology"}],"abstract":"This paper surveys the recent work in the intersection of differential privacy (DP) and fairness. It focuses on surveying the work observing that DP systems may exacerbate bias and disparate impacts for different groups of individuals. The survey reviews the conditions under which privacy and fairness may be aligned or contrasting goals, analyzes how and why DP exacerbates bias and unfairness in decision problems and learning tasks, and reviews the available solutions to mitigate 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.","doi":"10.24963/ijcai.2022/766","url":"https://ijcai.org/proceedings/2022/766","pdf":"https://ijcai.org/proceedings/2022/0766.pdf","markdown":"https://ijcai.org/proceedings/2022/766.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/766","volume":{"slug":"2022","title":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2022","url":"https://ijcai.org/proceedings/2022/","year":2022,"location":"Vienna","dates":"23-29 July 2022","editors":"Luc De Raedt","isbn":"978-1-956792-00-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2022"},"section":"Survey Track","track":"Survey Track","number":766,"pages":{"first":5470,"last":5477},"keywords":["Survey Track: AI Ethics, Trust, Fairness","Survey Track: Machine Learning"],"videos":[{"label":"Video #1","url":"https://slideslive.com/38987290","length_sec":102,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38985433","length_sec":723,"provider":"slideslive"}],"references":[{"position":1,"raw":"[Abadi et al., 2016] Martín Abadi, Andy Chu, Ian J. 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