The Quantified Worker

Erscheinungsjahr 2023
ISBN: 978-1-316-63695-4
Verlag: Cambridge University Press

Buch, Englisch, 250 Seiten, Format (B × H): 150 mm x 228 mm, Gewicht: 616 g

The information revolution has ushered in a data-driven reorganization of the workplace. Big data and AI are used to surveil workers and shift risk. Workplace wellness programs appraise our health. Personality job tests calibrate our mental state. The monitoring of social media and surveillance of the workplace measure our social behavior. With rich historical sources and contemporary examples, The Quantified Worker explores how the workforce science of today goes far beyond increasing efficiency and threatens to erase individual personhood. With exhaustive detail, Ifeoma Ajunwa shows how different forms of worker quantification are enabled, facilitated, and driven by technological advances. Timely and eye-opening, The Quantified Worker advocates for changes in the law that will mitigate the ill effects of the modern workplace.

Autoren/Hrsg.

Ajunwa, Ifeoma

Fachgebiete

• Rechtswissenschaften Arbeitsrecht

Inhaltsverzeichnis

Part I. The Ideology of Worker Quantification: 1. The Rise of Scientific Management; 2. Socio-Legal Responses to Scientific Management; Part II. The Mechanical Managers: 3. Automated Hiring and Discrimination; 4. Personality Job Tests; 5. Automated Video Interviews; 6. The Unbounded Workplace and Worker Surveillance; 7. Workplace Wellness Programs; 8. Telecommuting and Health Surveillance in the Covid-19 Era; Part III. Quantified Discrimination: 9. Wearable Tech: The Quantified Self at Work; 10. Quantified Racism; Part IV. Business Ethics and New Legal Frameworks: 11. The Ethical Dimensions of Worker Quantification; 12. Regulating Mechanical Managers; Conclusion: Imagining a Better Future for Workers.

Über Autor(innen)

Ajunwa, Ifeoma
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.