The philosophical basis of algorithmic recourse

Suresh Venkatasubramanian, Mark Alfano

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

Abstract

Philosophers have established that certain ethically important values are modally robust in the sense that they systematically deliver correlative benefits across a range of counterfactual scenarios. In this paper, we contend that recourse - the systematic process of reversing unfavorable decisions by algorithms and bureaucracies across a range of counterfactual scenarios - is such a modally robust good. In particular, we argue that two essential components of a good life - temporally extended agency and trust - are underwritten by recourse. We critique existing approaches to the conceptualization, operationalization and implementation of recourse. Based on these criticisms, we suggest a revised approach to recourse and give examples of how it might be implemented - especially for those who are least well off.

Original languageEnglish
Title of host publicationFAT* '20
Subtitle of host publicationproceedings of the 2020 Conference on Fairness, Accountability, and Transparency
Place of PublicationNew York
PublisherAssociation for Computing Machinery, Inc
Pages284-293
Number of pages10
ISBN (Electronic)9781450369367
DOIs
Publication statusPublished - Jan 2020
Event3rd ACM Conference on Fairness, Accountability, and Transparency, FAT* 2020 - Barcelona, Spain
Duration: 27 Jan 202030 Jan 2020

Conference

Conference3rd ACM Conference on Fairness, Accountability, and Transparency, FAT* 2020
CountrySpain
CityBarcelona
Period27/01/2030/01/20

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Keywords

  • algorithmic decision making
  • precarity
  • recourse
  • robust goods
  • Recourse
  • Precarity
  • Algorithmic decision making
  • Robust goods

Cite this

Venkatasubramanian, S., & Alfano, M. (2020). The philosophical basis of algorithmic recourse. In FAT* '20: proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (pp. 284-293). New York: Association for Computing Machinery, Inc. https://doi.org/10.1145/3351095.3372876