Discrimination by Algorithm: Employer Accountability for Biased Customer Reviews

Document Type

Article

Publication Title

UCLA Law Review

Journal Abbreviation

UCLA L. Rev.

Abstract

From Uber to Home Depot to Starbucks, companies are increasingly asking customers to rate workers. Gathering data from these ratings, many firms utilize algorithms to make employment decisions. The proliferation of customer ratings raises the possibility that some customers may review workers negatively for racist, sexist, or other illegal reasons. Absent a legal framework to address these changes, the expanding influence of consumer-sourced feedback threatens to undermine fundamental antidiscrimination protections for workers. This Article critically evaluates the legal regulation of customer-based, algorithmic discrimination in the workplace. The traditional view of customers as clients assumes that customers have no direct power to discipline or discharge workers. Yet today, online review systems allow customers to rate workers and decide their fates. Responding to these developments, this Article provides a method for understanding the rise of “managerial customers” and the legal responsibility that companies should assume for discriminatory customer reviews.

First Page

92

Last Page

153

Publication Date

2023

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