Assistant Professor at Department of Electrical & Electronics Engineering, Shri Ramswaroop Memorial University, Barabanki, Uttar Pradesh, India
Assistant Professor at School of Legal Studies, Babu Banarasi Das University, Lucknow, Uttar Pradesh, India
This research article presents a novel framework for analyzing the multifaceted impact of artificial intelligence (AI) on legal systems and the future of professional work. Moving beyond a monolithic view of technological disruption, it argues that the challenges posed by Autonomous AI Agents manifest along two distinct vectors: overt, confrontational threats and covert, integrative transformations. The first vector encompasses the “algorithmic panopticon”-highly visible applications like predictive policing and automated workforce surveillance that frontally challenge principles of due process, privacy, and labor rights. Conversely, the second vector involves a subtler, “accommodationist” creep, wherein agentic AI is woven into the fabric of daily professional practice. Tools for e-discovery and “robo-mediation” support do not just augment human capability; they gradually reshape legal reasoning, normalize algorithmic decision-making, and risk displacing essential human skills. By synthesizing analyses of AI in policing, alternative dispute resolution (ADR), and democratic governance, this paper maps this dual-front challenge, using the Indian context as a critical case study for workforce transformation. It concludes that while overt threats garner more scrutiny, the insidious nature of covert integration may pose a more profound, long-term risk to both institutional resilience and the future of meaningful human work.
Research Paper
International Journal of Law Management and Humanities, Volume 8, Issue 4, Page 1974 - 1984
DOI: https://doij.org/10.10000/IJLMH.1110648This 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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