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Labor Economics Of Autonomous Agent Integration: Displacement And Creation




Nitesh Kumar Dubey, Assistant Professor, School of Legal Studies, Babu Banarasi Das University, Lucknow, Uttar Pradesh, India


ABSTRACT


The integration of autonomous agents into the global workforce marks a pivotal ontological shift from reactive “Generative AI” to proactive, goal-oriented “Agentic AI,” fundamentally altering the labor-capital compact. This article provides an exhaustive analysis of the labor economics driving this transition, contrasting the diminishing “reinstatement effect” of new task creation against the accelerating “displacement effect” of algorithmic substitution. We investigate the “Turing Trap,” where excessive investment in human-mimicking automation leads to the “unbossing” of middle management and the hollowing out of cognitive professions, potentially stagnating total factor productivity (TFP). Simultaneously, we explore the evolution of employment law from the 20th-century Industrial Relations model to the nascent regime of “Algorithmic Management.” We analyze how the “fissured workplace” allows firms to use agents to exert direct control over workers while evading legal liability, challenging doctrines of respondeat superior and fiduciary duty. By synthesizing global case studies- from “digital colonialism” in the Global South to “technowelfare” in Japan- this article proposes a new regulatory framework centered on “Human-in-Command” principles and “duty-bearing” legal status for AI, ensuring that the rise of autonomous agents serves to reinstate, rather than obsolete, the value of human labor.


Keywords: Autonomous Agents, Algorithmic Management, Reinstatement Effect, Respondeat Superior, Digital Taylorism, Turing Trap




Indian Journal of Law and Legal Research

Abbreviation: IJLLR

ISSN: 2582-8878

Website: www.ijllr.com

Accessibility: Open Access

License: Creative Commons 4.0

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All research articles published in The Indian Journal of Law and Legal Research are fully open access. i.e. immediately freely available to read, download and share. Articles are published under the terms of a Creative Commons license which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

 

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The opinions expressed in this publication are those of the authors. They do not purport to reflect the opinions or views of the IJLLR or its members. The designations employed in this publication and the presentation of material therein do not imply the expression of any opinion whatsoever on the part of the IJLLR.

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