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Original Article

AI-generated Content and Copyright Authorship: Tracing India’s Human-Authorship Standard against Generative AI

Open Access Peer Reviewed Crossref DOI

Authors

  • Avish Kumar1

1 B.B.A. LL.B. (Hons.), Indore Institute of Law, Devi Ahilya Vishwavidyalaya, Madhya Pradesh, India.

Article Information

Published Online
July-August 2026
Pages
188-192
Article Type
Original Article
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Abstract

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This article examines the unresolved legal status of AI-assisted copyright authorship in India, centred on the Suryast artwork episode. In November 2020, the Indian Copyright Office briefly registered the AI system ‘RAGHAV’ as a co-author alongside human applicant Ankit Sahni, but subsequently issued an unexplained withdrawal notice. This administrative silence has persisted for over five years, creating a legal vacuum despite India possessing Section 2(d)(vi) of the Copyright Act 1957, a provision specifically designating the author of a computer-generated work as the person who “causes the work to be created”. The paper contrasts India’s statutory framework with the strict human-authorship standard maintained by the United States and highlights the divergent international administrative treatment of the Suryast artwork. Doctrinally, the article analyses how India’s ‘modicum of creativity’ standard applies to generative AI outputs, questioning whether parameter-tuning and prompting constitute sufficient human contribution. It further explores the statutory incompatibility of naming AI as a joint author under Section 2(z) of the Act, which excludes software from the definition of a ‘person’. Finally, the article outlines downstream copyright issues, including training-data infringement, ownership mapping, and moral rights that remain paralyzed by the unresolved authorship question. Concluding with a comparative analysis of the United Kingdom and the United States, the author argues that India’s supposedly AI-ready statute remains practically unsettled. The article calls for a reasoned administrative order, a judicial test case, or a legislative amendment to clarify the boundaries of computer-generated authorship in the generative AI era.

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