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Judicial Interpretation Of AI-Generated Works Under Copyright Law




Aryan Leander Wishard


ABSTRACT


Copyright law has always had to absorb new creative technologies, from the camera to the photocopier to the computer. Generative artificial intelligence is the most disruptive of these technologies yet, because it does not merely assist human creativity but, in certain configurations, appears to substitute for it entirely. This essay examines how courts and the United States Copyright Office have interpreted copyright protection for AI-generated works against the backdrop of foundational authorship doctrine. Beginning with the human authorship requirement as settled by the Thaler v. Perlmutter litigation and the Copyright Office’s 2023 guidance, the essay examines how the partially protected Zarya of the Dawn graphic novel illustrates the emerging “sufficient human control” standard. It then turns to the fair use and training-data questions raised by Andersen v. Stability AI and The New York Times Co. v. Microsoft, and considers the right of publicity gap exposed by AI style mimicry. The essay concludes with a comparative survey of the United Kingdom, European Union, and Indian approaches, and argues that while the bedrock requirement of human authorship is now clear, the line between mere use of an AI tool and genuine human authorship in AI-assisted works remains the central unresolved question in copyright law.


Keywords: Copyright Law, AI-Generated Works, Authorship Doctrine, Sufficient Human Control, Human Authorship




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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