Incentives to Offer Algorithmic Recourse

Matthew Olckers, Toby Walsh
1/27/2023
cs.GTcs.AI

No confident code implementation found for this paper.

Abstract

Due to the importance of artificial intelligence (AI) in a variety of high-stakes decisions, such as loan approval, job hiring, and criminal bail, researchers in Explainable AI (XAI) have developed algorithms to provide users with recourse for an unfavorable outcome. We analyze the incentives for a decision-maker to offer recourse to a set of applicants. Does the decision-maker have the incentive to offer recourse to all rejected applicants? We show that the decision-maker only offers recourse to all applicants in extreme cases, such as when the recourse process is impossible to manipulate. Some applicants may be worse off when the decision-maker can offer recourse.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{olckers2023incentives,
  title  = {Incentives to Offer Algorithmic Recourse},
  author = {Matthew Olckers and Toby Walsh},
  year   = {2023},
  eprint = {2301.12884},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2301.12884v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2301.12884.svg)](https://codeofpaper.com/paper/2301.12884)

Discussion