Article

People underestimate the errors by algorithms for credit scoring and recidivism but tolerate even fewer errors

2021-03-22

Abstract excerpt

<p>This study provides the first representative analysis of error estimations and error tolerance in a Western country (Germany) with regards to algorithmic decision-making systems (ADM). We examine people’s expectations about the accuracy of algorithms that predict credit default, recidivism of an offender, suitability of a job applicant, and health behavior. Also, we ask whether expectations about algorithm erro...

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Literature Corpus work: 5474e465-aa56-51f1-9fb4-1fd47f1e8a37
DOI: 10.31234/osf.io/kq8ra

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