preprintJan 9, 2019GREEN OA

Actionable Recourse in Linear Classification

Harvard University Press · Carnegie Mellon University · +1 more institution

Indexed inarxivcrossref

Abstract

Classification models are often used to make decisions that affect humans: whether to approve a loan application, extend a job offer, or provide insurance. In such applications, individuals should have the ability to change the decision of the model. When a person is denied a loan by a credit scoring model, for example, they should be able to change the input variables of the model in a way that will guarantee approval. Otherwise, this person will be denied the loan so long as the model is deployed, and -- more importantly --will lack agency over a decision that affects their livelihood.

Citation impact

447
total citations
FWCI
33.22
Percentile
100%
References
63
Citations per year

Authors

3

Topics & keywords

Keywords
  • Loan
  • Computer science
  • Affect (linguistics)
  • Livelihood
  • Integer programming
  • Frame (networking)
  • Marital status
  • Linear programming
UN Sustainable Development Goals
  • No poverty
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