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9781316636954

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'Work is a meaningful part of our lives, in time and in quality. Yet, as Ifeoma Ajunwa's new book masterfully shows, our work lives are under almost totalizing surveillance, for the benefit of employers. With clarity and care, Dr. Ajunwa shows us the extent to which employers have insinuated into every second of our days. Her book teaches us what we risk in the face of worker quantification and offers a bold and morally rich plan for tackling it, for the good of all of us.' Danielle Keats Citron, 2019 MacArthur Fellow, author of The Fight for Privacy 'Scientific management is not new, but as Dr. Ajunwa eloquently and definitively argues, the technologically-mediated quantification of the American worker poses novel and consequential challenges for labor, equity, and democracy itself. The Quantified Worker is a meticulous and passionate call to action, an urgent plea for a robust response from our legal system.' Virginia Eubanks, author of Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor 'Ajunwa's treatment of worker's rights - and lack thereof - in the context of corporate surveillance is critical, timely, and profound. It will be an invaluable resource to lawyers trying to understand the comprehensive reach of workplace monitoring and measuring, to data scientists trying to understand the relevant law in their fields, and to anyone else who wants to interrogate the AI marketing hype.' Cathy O'Neil, author of Weapons of Math Destruction 'The surveillance and quantification of workers is a critical issue of our time. This much-needed book details how these technologies erode labor rights and encode discrimination, and it's powerful evidence for why we need worker coalitions and strong legal protections.' Kate Crawford, USC Annenberg, author of Atlas of AI

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Ifeoma Ajunwa is a 2021-2022 Fulbright Scholar, an award-winning tenured law professor at the University of North Carolina School of Law, and adjunct professor at the Kenan-Flagler Business School. She is the Founding Director of the Artificial Intelligence Decision-Making Research Program and a Faculty Associate at the Berkman Klein Centre at Harvard University.

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