{"type":"ScholarlyArticle","title":"Incentivizing Recourse through Auditing in Strategic Classification","authors":[{"name":"Andrew Estornell","slug":"andrew-estornell","given":"Andrew","family":"Estornell","affiliation":"Washington University in Saint Louis"},{"name":"Yatong Chen","slug":"yatong-chen","given":"Yatong","family":"Chen","affiliation":"University of California Santa Cruz"},{"name":"Sanmay Das","slug":"sanmay-das","given":"Sanmay","family":"Das","affiliation":"George Mason University"},{"name":"Yang Liu","slug":"yang-liu","given":"Yang","family":"Liu","affiliation":"University of California Santa Cruz"},{"name":"Yevgeniy Vorobeychik","slug":"yevgeniy-vorobeychik","given":"Yevgeniy","family":"Vorobeychik","affiliation":"Washington University in Saint Louis"}],"abstract":"The increasing automation of high-stakes decisions with direct impact on the lives and well-being of individuals raises a number of important considerations. Prominent among these is strategic behavior by individuals hoping to achieve a more desirable outcome. Two forms of such behavior are commonly studied: 1) misreporting of individual attributes, and 2) recourse, or actions that truly change such attributes. The former involves deception, and is inherently undesirable, whereas the latter may well be a desirable goal insofar as it changes true individual qualification. We study misreporting and recourse as strategic choices by individuals within a unified framework. In particular, we propose auditing as a means to incentivize recourse actions over attribute manipulation, and characterize optimal audit policies for two types of principals, utility-maximizing and recourse-maximizing. Additionally, we consider subsidies as an incentive for recourse over manipulation, and show that even a utility-maximizing principal would be willing to devote a considerable amount of audit budget to providing such subsidies. Finally, we consider the problem of optimizing fines for failed audits, and bound the total cost incurred by the population as a result of audits.","doi":"10.24963/ijcai.2023/45","url":"https://ijcai.org/proceedings/2023/45","pdf":"https://ijcai.org/proceedings/2023/0045.pdf","markdown":"https://ijcai.org/proceedings/2023/45.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/45","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"AI Ethics, Trust, Fairness","track":"Main Track","number":45,"pages":{"first":400,"last":408},"keywords":["AI Ethics, Trust, Fairness: ETF: Safety and robustness","Game Theory and Economic Paradigms: GTEP: Other","AI Ethics, Trust, Fairness: ETF: Societal impact of AI"],"videos":[],"references":[{"position":1,"raw":"[Barsotti et al., 2022] Flavia Barsotti, Rüya Gökhan Koc ¸er, and Fernando P Santos. 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