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Artificial Intelligence And Criminal Liability: Rethinking Mens Rea In The Age Of Autonomous Systems




Advocate Ritika Sharma, LL.M., Fairfield Institute of Management and Technology, Guru Gobind Singh Indraprastha University (GGSIPU)


ABSTRACT


As Artificial Intelligence (AI) continues its exponential evolution, it challenges traditional legal doctrines built around human agency, culpability, and intent. The cornerstone of criminal liability mens rea requires a conscious, culpable mental state, but AI systems operate through sophisticated algorithms, neural networks, and deep learning models, entirely devoid of human consciousness or subjective intent. This article explores the conceptual and legal complexities surrounding the attribution of criminal liability for harms caused by highly autonomous systems. It critically examines why existing legal frameworks, particularly in the Indian context, are insufficient and explores proposed models, such as Synthetic Mens Rea and Vicarious Liability. Drawing from comparative international perspectives, this study seeks to provide a balanced understanding of how criminal jurisprudence must adapt in the digital age by advocating for a hybrid framework that bridges the growing accountability gap between human creators and autonomous agents.


Keywords: Artificial Intelligence, Criminal Liability, Mens Rea, Autonomous Systems, Legal Reform, Legal Personhood



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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Licensing: 

 

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.

 

Disclaimer:

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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