Several times each month, we are pleased to republish a recent book review from the Canadian Law Library Review (CLLR). CLLR is the official journal of the Canadian Association of Law Libraries (CALL/ACBD), and its reviews cover both practice-oriented and academic publications related to the law.
The Quantified Worker: Law and Technology in the Modern Workplace. By Ifeoma Ajunwa. Cambridge, U.K.: Cambridge University Press, 2023. xiv, 461 p. Includes bibliographic references, illustrations, and index. ISBN 9781316636954 (softcover) $39.95.
Reviewed by Alexandra Kwan
Digital Services and Reference Librarian
Bora Laskin Law Library
University of Toronto
The Quantified Worker begins like a dystopian science fiction story. To get the job, a worker is subjected to interviews conducted by an automated hiring platform, personality quizzes to assess her mental state, and genetic testing to participate in the employer’s wellness program. To keep her job, she wears a device to track the most intimate details of her health, performs for a mechanical manager, and all her movements are tracked. The twist? All of this is already here, thanks to “surveillance capitalism,” in which workers’ “every move [is] tracked and monitored in service of profit-making” (p. 2).
This bleak present is shown to us by author Ifeoma Ajunwa, a professor of law at Emory University and the founding director of its AI and the Law Program. An award-winning law and technology scholar, Ajunwa’s research focuses on “ethical governance, privacy, and discrimination issues in workplace AI and automated decision-making technologies.”[1] In The Quantified Worker, Ajunwa deftly distills the ways in which technologies based on AI and big data impact workers, while also providing some law-based solutions.
The book comprises 12 chapters in four parts. The first two chapters in Part 1 explain Taylorism and Scientific Management theory and provide a brief legal history of labour relations in the U.K. and U.S. (noting key cases and legislation). The next six chapters address the use of mechanical managers during worker recruitment, and then surveillance once the worker is hired. So-called “neutral” automated hiring platforms use flawed algorithms that perpetuate a lack of diversity in organizations by selecting candidates based on “cultural fit” (Chapter 3). Seemingly innocuous workplace personality tests end up functioning as medical exams and cultural knowledge tests, disadvantaging neurodiverse and racialized candidates (Chapter 4). Ajunwa points out the inherent bias found in facial analysis and emotion recognition used in automated video interviewing platforms, which mirrors the well-known problems with phrenology (Chapter 5). Chapters 6–8 address surveillance experienced by workers in the physical workplace or while telecommuting, in wellness programs, and during the COVID-19 era.
The next two chapters make up Part III: Quantified Discrimination. These chapters are about wearable technologies (Chapter 9) and racial quantification (Chapter 10). Although these chapters are adapted from Ajunwa’s earlier work, they have been expanded and updated for this publication.
The final part of the book discusses ethics and ways to regulate these technologies. Ajunwa uses Rawls’s Theory of Justice to explore “meaningful work,” the worker–employer power dynamic, and gig work (Chapter 11). Chapter 12 draws upon Ajunwa’s previous work and provides potential solutions to solve the workplace issues caused by mechanical managers. Notably, Ajunwa calls for “concurrent regulation” in which “[g]overmental regulation of automated decision-making can and should exist alongside industry regulation” (p. 350). She proposes a change to Title VII of the U.S. Civil Rights Act of 1964 in addition to external audits of algorithms conducted by a third-party certifying body (like how LEED certification is used in the building industry). Ajunwa provides a critical analysis of a bill not yet passed by the U.S. Congress to address the discriminatory effects of workplace automated decision-making systems. [2]
The Quantified Worker could easily be read together with Brishen Rogers’s Data and Democracy at Work: Advanced Information Technologies, Labor Law, and the New Working Class, which was published in the same year by another academic press.[3] 7 Rogers is also a law professor, whose book covers similar areas. Both texts provide historical context for the modern North American workplace, discuss Taylorism, and propose reforms for workers and policymakers. Also, both scholars have cited each other’s prior work in their respective books. However, Ajunwa’s book provides more analysis and content relating to racial discrimination and ableism stemming from employers’ use of AI systems and big data. Rogers’s work is more theoretical and focuses more on technology’s role in dominating the working class. The Quantified Worker is organized by the types of workplace programs and hiring activities familiar to workers, and thus individual chapters could stand independently as course readings or practical entry points for a more diverse range of readers who want to learn more about a particular area.
This book’s organization and topic lends itself to a wide readership. The Quantified Worker is a natural fit in academic library collections that cater to scholars in law, industrial relations, information studies, and other disciplines. However, it would be a welcome addition to public libraries’ collections since any worker or employer may wish to learn how these technologies are shaping the modern workplace. Although the book focuses on American law, Canadian law firm libraries could consider adding this title since it may provide another perspective as Canada similarly embarks on regulating these technologies.[4]
The Quantified Worker covers much ground: it points to scholarly research and provides historical context and analysis of case law and legislation. However, Ajunwa’s use of well-placed narrative and illustrative examples make it a compelling and meaningful read for anyone looking to learn more about the impact of AI and big data technologies in the workplace.
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[1] Emory University School of Law, “Ifeoma Ajunwa” (last visited 9 March 2024), online:
[2] The U.S. Algorithmic Accountability Act 2022 was reintroduced in 2023. At the time of writing this review, the bill has been referred to committee stage at both levels of Congress.
[3] Brishen Rogers, Data and Democracy at Work: Advanced Information Technologies, Labor Law, and the New Working Class (Cambridge, Mass: MIT Press, 2023).
[4] Bill C-27, An Act to enact the Consumer Privacy Protection Act, the Personal Information and Data Protection Tribunal Act and the Artificial Intelligence and Data Act and to make consequential and related amendments to other Acts, 1st Sess, 44th Parl, 2024 (at consideration in committee in the House of Commons, at the time of writing this review).
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