Challenges Of Copyright Protection For AI- Generated Content: A Comparative Study Of India And Australia
- IJLLR Journal
- 4 days ago
- 2 min read
Anshika Kapoor, B.B.A. LL.B., Bharati Vidyapeeth University
ABSTRACT
The emergence of generative artificial intelligence systems capable of producing literary, artistic, musical, and audiovisual works of considerable sophistication has exposed a structural fault line in the architecture of copyright law as it exists in virtually every jurisdiction in the world. Copyright doctrine is built on the premise of human authorship: the author is the natural person whose intellectual creativity gives rise to the work, and the rights the law grants are conceived as a form of recognition and incentive directed at that creative person. Generative AI disaggregates this premise by introducing a technological intermediary whose outputs are produced through processes that may involve no human creative decision-making at the point of generation, even where the system was trained on human- authored works and is operated through human-crafted prompts. This paper undertakes a comparative analysis of how the copyright frameworks of India and Australia two common law jurisdictions with shared colonial legislative heritage but diverging approaches to the challenge of computer-generated works address this problem, and what each jurisdiction's approach reveals about the adequacy of existing copyright doctrine in the age of generative AI. It examines the statutory definitions of authorship in the Copyright Act, 1957 (India) and the Copyright Act, 1968 (Cth) (Australia), the judicial development of originality standards in both jurisdictions, the treatment of computer-generated works under each Act, and the emerging questions regarding ownership, moral rights, and the use of copyright works for AI training. The paper identifies three central challenges: the authorship gap, which arises when AI generates works without sufficient human creative contribution to satisfy the originality requirement; the ownership problem, which concerns the allocation of any rights that do subsist between the developer of the AI system, the operator, and the user who provides the prompt; and the training data question, which asks whether the ingestion of copyright works to train AI models constitutes infringement of reproduction rights. The paper concludes that both India and Australia require legislative reform to address these challenges, and offers a comparative assessment of the reform options available to each jurisdiction.
Keywords: Copyright; Artificial Intelligence; AI-Generated Content; Authorship; Originality; Copyright Act 1957; Copyright Act 1968; India; Australia; Generative AI.
