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Artificial Intelligence, Big Data, Algorithmic Management, and Labor Law

Document Type

Book Section

Publication Date

2024

Publication Title

The Oxford Handbook of the Law of Work

Abstract

Employers are increasingly relying on algorithms and AI to manage their workforces, using automated systems to recruit, screen, select, supervise, discipline, and even terminate employees. This chapter explores the effects of these systems on the rights of workers in standard work relationships, who are presumptively protected by labor laws. It examines how these new technological tools affect fundamental worker interests and how existing law applies, focusing primarily as examples on two particular concerns—nondiscrimination and privacy. Although current law provides some protections, legal doctrine has largely developed with human managers in mind, and as a result, fails to fully apprehend the risks posed by algorithmic tools. Thus, while anti-discrimination law prohibits discrimination by workplace algorithms, the existing framework has a number of gaps and uncertainties when applied to these systems. Similarly, traditional protections for employee privacy are ill-equipped to address the sheer volume and granularity of worker data that can now be collected, and the ability of computational techniques to extract new insights and infer sensitive information from that data. More generally, the expansion of algorithmic management affects other fundamental worker interests because it tends to increase employer power vis à vis labor. This chapter concludes by briefly considering the role that data protection laws might play in addressing the risks of algorithmic management.

Keywords

Artificial Intelligence, AI, Big Data, Algorithmic Management, People Analytics, Employment Discrimination, Employee Privacy, Labor Standards, Labor Law, Data Protection

Publication Citation

Pauline Kim, Artificial Intelligence, Big Data, Algorithmic Management, and Labor Law in The Oxford Handbook of the Law of Work. (Forthcoming, 2024) [Oxford University Press]

Comments

ISBN: 9780192870360

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