Employment Law Evolution: From Industrial Relations to Algorithmic Management

  • Nitesh Kumar Dubey
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  • Nitesh Kumar Dubey

    Assistant Professor at School of Legal Studies, Babu Banarasi Das University, Lucknow, Uttar Pradesh, India

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Abstract

The trajectory of employment law has historically mirrored the dominant modes of production, evolving from the master-servant doctrines of the pre-industrial era to the collective bargaining frameworks of the Fordist industrial age. However, the contemporary workplace is undergoing a seismic shift driven by the datafication of labor and the ascendancy of Algorithmic Management (AM). This article provides an exhaustive analysis of this legal and operational evolution, tracing the lineage from scientific management (Taylorism) to its digital reincarnation (“Digital Taylorism”). It critically examines how the rise of algorithmic control- characterized by pervasive surveillance, automated decision-making (ADM), and the fissuring of the workplace- challenges the foundational assumptions of industrial relations systems designed for human-centric hierarchies. Through a comparative legal analysis of the European Union, the United States, and emerging economies such as India and China, the article explores the regulatory lag in addressing algorithmic bias, automated termination, and the classification of platform workers. Furthermore, it posits that the future of labor law lies in the reconceptualization of data rights as collective labor rights, necessitating a new paradigm of “algorithmic collective action” and co-enforcement mechanisms to bridge the widening gap between technological capability and worker protection.

Keywords

  • Employment Law
  • Algorithmic Management
  • Industrial Relations
  • Digital Taylorism
  • Platform Work Directive
  • Collective Bargaining
  • Workplace Surveillance
  • Artificial Intelligence
  • Data Rights
  • Fissured Workplace.

Type

Research Paper

Information

International Journal of Law Management and Humanities, Volume 8, Issue 6, Page 652 - 664

DOI: https://doij.org/10.10000/IJLMH.1111133

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This is an Open Access article, distributed under the terms of the Creative Commons Attribution -NonCommercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/), which permits remixing, adapting, and building upon the work for non-commercial use, provided the original work is properly cited.

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