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Training AI On Copyright Works: Is India Moving Towards a Compulsory Licensing Regime?




Ananya Karan, Maharaja Agrasen Institute of Management Studies, GGSIPU


ABSTRACT


The rapid development of generative artificial intelligence (AI) has led to the worldwide debate of the legality of training AI models on copyrighted content. The US goes mostly by the principle of fair use, the European Union has a kind of opt out system, and India has taken a different path altogether. In a move that kind of surprised everyone, India backed a royalty - based compulsory blanket licensing system called One Nation, One Licence, One Payment Model (ONLP) by which AI developers must pay copyright owners every time they use their works for AI training purposes.


This piece delves into the regulatory landscape that India is trying to create around generative AI (GAI), looking at the legal basis, economic consequences, and policy aims of the government. Locating India's position relative to the other global frameworks and the court rulings as they are progressing, the article points out that compulsory licensing would theoretically give licensing rights and thus creators the upper hand and also clear up regulatory issues, but at the same time such a measure would be associated with higher innovation costs, the problem of administration, and the trouble of getting approval at the level of constitutional law.


Keywords: AI models, Copyright, Generative AI, Global Framework, Legality, AI Training.



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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