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Legal Challenges Of AI-Generated Content: A Critical Analysis Of Copyright Protection And Consumer Rights In India




Ritika Yadav, Amity University, Uttar Pradesh


ABSTRACT


The rapid proliferation of artificial intelligence systems capable of generating text, images, audio, and video has raised complex legal questions that challenge traditional frameworks of copyright protection and consumer rights. This dissertation critically examines the legal challenges posed by AI- generated content in India, with a particular focus on the adequacy of existing copyright law and consumer protection mechanisms.


The study adopts a doctrinal and analytical methodology, examining statutory provisions, judicial decisions, comparative legal developments, and policy documents. It analyses core copyright doctrines such as originality, authorship, ownership, moral rights, and infringement, and evaluates their applicability to AI-generated content. The dissertation also explores the legal implications of using copyrighted works as AI training data and assesses the scope and limitations of fair dealing under Indian law.


Beyond copyright, the research investigates consumer harms arising from AI-generated content, including deception, deepfakes, fake reviews, and automated persuasion. It evaluates the effectiveness of the Consumer Protection Act, 2019, and intermediary liability frameworks in addressing such harms, with particular attention to platform accountability and disclosure obligations.



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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