Legal Recognition And Ownership Of AI- Generated Works Under Indian Copyright Law
- IJLLR Journal
- 14 minutes ago
- 2 min read
Priyadharshini G, LL.M., CHRIST (Deemed to be University), Bengaluru.
Prof. Dr. Valarmathi R, CHRIST (Deemed to be University), Bengaluru.
ABSTRACT
The rapid advancement of generative artificial intelligence has fundamentally altered the landscape of creative production, posing unprecedented challenges to traditional copyright frameworks that are grounded in human authorship and individual creative expression. As generative systems increasingly produce literary, artistic, musical, and audiovisual outputs with minimal or indirect human intervention, existing legal doctrines struggle to accommodate questions of originality, authorship, ownership, and liability. This research critically examines how generative artificial intelligence disrupts foundational principles of copyright law and evaluates the adequacy of current legal responses to these emerging complexities. The study explores the conceptual tension between human- centric originality standards and machine-generated creativity, highlighting the doctrinal uncertainty surrounding authorship attribution in AI-assisted and AI-generated works. It further analyzes competing claims of ownership among developers, deployers, and users of generative systems, demonstrating how traditional ownership rules fail to provide clarity in algorithm-driven creative processes. Particular attention is paid to copyright infringement risks arising from the use of protected works in AI training datasets and the potential for infringing outputs, raising complex questions of direct, secondary, and intermediary liability. In addition to legal uncertainty, the research addresses broader ethical and socio-legal concerns, including transparency, accountability, bias, and the erosion of human creative labour. A comparative analysis of legal developments in jurisdictions such as India, the United States, the United Kingdom, and the European Union reveals fragmented and often inconsistent regulatory approaches to generative AI. Against this backdrop, the study argues for a balanced, human-centric regulatory framework that safeguards authors’ rights while fostering innovation. It proposes policy reforms emphasising transparency in training practices, calibrated liability standards, and statutory mechanisms to reconcile technological advancement with the normative objectives of copyright law.
Keywords: Copyright law, Generative Artificial Intelligence, Ownership, Copyright Infringement.
