Algorithms, Platforms, and Ethnic Bias: A Diagnostic Model

Abstract: 

Ethnic and other biases are increasingly recognized as a problem that plagues software algorithms and datasets. This is important because algorithms and digital platforms organize ever-greater areas of social, political, and economic life. Algorithms already sift through expanding datasets to provide credit ratings, serve personalized advertisements, match individuals on dating sites, flag unusual credit-card transactions, recommend news articles, determine mortgage qualification, predict the locations and perpetrators of future crimes, parse résumés, rank job candidates, assist in bail or probation proceedings, and perform a wide variety of other tasks. Digital platforms are comprised of algorithms executed in software. In performing these functions, as Lawrence Lessig observed, "code" functions like law in structuring human activity. Algorithms and online platforms are not neutral; they are built to frame and drive actions.

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Author: 
Selena Silva
Publication date: 
November 1, 2019
Publication type: 
Journal Article
Citation: 
Silva, S., & Kenney, M. (2019, November 1). Algorithms, Platforms, and Ethnic Bias. November 2019 | Communications of the ACM. https://cacm.acm.org/magazines/2019/11/240361-algorithms-platforms-and-ethnic-bias/fulltext