Algorithms, Platforms, and Ethnic Bias: A Diagnostic Model

Communications of the Association of Computing Machinery, Forthcoming November 2019

9 Pages Posted: 7 Aug 2019

See all articles by Silva Selena

Silva Selena

Independent

Martin Kenney

University of California, Davis

Date Written: August 2, 2019

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 composed of algorithms executed in software. In performing these functions, as Lawrence Lessig observed, “code” functions like law to structure human activity. Algorithms and online platforms are not neutral; they are built to frame and drive actions. Algorithmic “machines” are built with specific theories about the correspondences between persons and things in mind. Concerns are becoming more acute, as techniques such as machine learning, are more generally deployed. For engineers and policy makers alike, understanding how and where bias occurs in algorithmic processes can help address it. Our contribution is the introduction of a visual model that extends previous research to identify where in an algorithmic process bias may occur.

Keywords: algorithms, digital bias, digital discrimination, platform economy, racism

Suggested Citation

Selena, Silva and Kenney, Martin, Algorithms, Platforms, and Ethnic Bias: A Diagnostic Model (August 2, 2019). Communications of the Association of Computing Machinery, Forthcoming November 2019, Available at SSRN: https://ssrn.com/abstract=3431468

Silva Selena

Independent ( email )

Martin Kenney (Contact Author)

University of California, Davis ( email )

Community and Regional Development Unit
Davis, CA 95616
United States
5305745943 (Phone)

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