Abstract
The rise of digital commerce, consumer surveillance, and bigdata analytics have given rise to a new set of pricing techniques in the first quarter of the 21st century. Much has been made of algorithmic price discrimination—the commercial practice of charging consumers individualized prices for identical goods and services. Considerably less attention has been paid to parallel development in the world of work—the emergence of “algorithmic personalized wages” that individualize worker pay for identical work. Algorithmic personalized wages are not a significant development because they are ubiquitous in contemporary employment arrangements—they are not—but because they contain the kernel of a harsh future for workers. In this future, employers’ capacity to “drive a hard bargain” is expansive, pervasive, and supercharged by potent technologies which they alone control.
Where previous accounts of algorithmic personalized wages have emphasized antitrust law as a key point of reference for developing remedies, this Note proposes that consumer protection law, and in particular the law of unfair deceptive acts and practices (UDAPs), is similarly worthy of serious consideration. It argues that in the right circumstances, UDAP laws may provide a viable, if limited, method for deterring the spread of algorithmic personalized wages.
Volume
44
Issue
2
First Page
149
Page Number
149
DOI
https://doi.org/10.24926/25730037.738
Recommended Citation
Noah Madoff,
Unfair and Deceptive Pay: A Consumer Protection Approach to Algorithmic Personalized Wages,
44
L. & Inequality
149
(2026).
Available at:
https://scholarship.law.umn.edu/lawineq/vol44/iss2/5
Rights
http://rightsstatements.org/vocab/InC-EDU/1.0/
