The Algorithmic Leviathan: Arbitrariness, Fairness, and Opportunity in Algorithmic Decision-Making Systems

This article examines the complaint that arbitrary algorithmic decisions wrong those whom they affect. It makes three contributions. First, it provides an analysis of what arbitrariness means in this context. Second, it argues that arbitrariness is not of moral concern except when special circumstan...

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Bibliographic Details
Published in:Canadian journal of philosophy Vol. 52; no. 1; pp. 26 - 43
Main Authors: Creel, Kathleen, Hellman, Deborah
Format: Journal Article
Language:English
Published: Edmonton Cambridge University Press 01.01.2022
Subjects:
Algorithms
Arbitrariness
Automation
Decision making
Employers
Hiring
Randomized algorithms
ISSN:0045-5091, 1911-0820
Online Access:Get full text
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Summary:This article examines the complaint that arbitrary algorithmic decisions wrong those whom they affect. It makes three contributions. First, it provides an analysis of what arbitrariness means in this context. Second, it argues that arbitrariness is not of moral concern except when special circumstances apply. However, when the same algorithm or different algorithms based on the same data are used in multiple contexts, a person may be arbitrarily excluded from a broad range of opportunities. The third contribution is to explain why this systemic exclusion is of moral concern and to offer a solution to address it.
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ISSN:0045-5091
1911-0820
DOI:10.1017/can.2022.3