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Penology: An Insight Into The Framework Of Punishment For Artificial Intelligence




Shilpa Nayak, LLM Candidate, National Law University, Delhi.


Aditya Narayan Dwivedi, Legal Consultant, Graduated from National Law University, Odisha


ABSTRACT


The rapid advancement of artificial intelligence (AI) technology has introduced complex challenges to the field of penology, particularly concerning the framework of punishment for AI entities. This paper explores the theoretical and practical implications of holding AI systems criminally liable for their actions. It examines the foundational principles of criminal law, such as culpability and mens rea, and evaluates their applicability to AI. The discussion includes an analysis of various theories of punishment— deterrence, retribution, rehabilitation, and restorative justice—and their relevance to AI. The paper also considers alternative approaches, such as civil liability and regulatory measures, as potential solutions to AI-generated harms. By drawing parallels with corporate criminal liability, the study highlights the feasibility and limitations of extending traditional punitive measures to AI. Ultimately, the paper argues for a cautious and balanced approach, emphasizing the need for legal reforms that address the unique nature of AI while ensuring justice and public safety.

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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.

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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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