To Give or Not to Give? The Impacts of Strategically Withheld Recourse
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Abstract (arXiv)
Individuals often aim to reverse undesired outcomes in interactions with automated systems, like loan denials, by either implementing system-recommended actions (recourse), or manipulating their features. While providing recourse benefits users and enhances system utility, it also provides information about the decision process that can be used for more effective strategic manipulation, especially when the individuals collectively share such information with each other. We show that this tension leads rational utility-maximizing systems to frequently withhold recourse, resulting in decreased population utility, particularly impacting sensitive groups. To mitigate these effects, we explore the role of recourse subsidies, finding them effective in increasing the provision of recourse actions by rational systems, as well as lowering the potential social cost and mitigating unfairness caused by recourse withholding.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 20 of its 31 references that are in the map. First posted on arXiv 8 Apr 2025.
Builds on
20 of 31 references.
References · 20
- 2018Actionable Recourse in Linear Classificationcited by 328
- 2015Strategic Classificationcited by 257
- 2020Algorithmic recourse under imperfect causal knowledge: a probabilistic approachcited by 140
- 2017Strategic Classification from Revealed Preferencescited by 128
- 2020A survey of algorithmic recourse: definitions, formulations, solutions, and prospectscited by 118
- 2018The Social Cost of Strategic Classificationcited by 105
- 2018The Disparate Effects of Strategic Manipulationcited by 75
- 2020On the Fairness of Causal Algorithmic Recoursecited by 70
- 2021Strategic Classification Made Practicalcited by 59
- 2019Equalizing Recourse across Groupscited by 55
- 2021Who Leads and Who Follows in Strategic Classification?cited by 53
- 2021Information Discrepancy in Strategic Learningcited by 48
8 more
- 2018Strategyproof Linear Regression in High Dimensionscited by 22
- 2019Optimal Decision Making Under Strategic Behaviorcited by 20
- 2020Linear Classifiers that Encourage Constructive Adaptationcited by 16
- 2021Bayesian Persuasion for Algorithmic Recoursecited by 14
- 2023Robustness Implies Fairness in Causal Algorithmic Recoursecited by 12
- 2021Model Transferability With Responsive Decision Subjectscited by 9
- 2023The Risks of Recourse in Binary Classificationcited by 8
- 2016Price of Transparency in Strategic Machine Learningcited by 6
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Citing papers per year: 2026: 2.
2 papers.