AUTHORSHIP AND OWNERSHIP IN AI GENERATED WORKS: RETHINKING COPYRIGHT IN THE AGE OF ARTIFICIAL INTELLIGENCE
Zhil Manek, 10th Semester B.A.LL.B Student at MKES College of Law, Mumbai (India)
“The growing use of artificial intelligence as a creative tool has introduced significant challenges for copyright law, which has historically been based on the idea of human authorship. Today, AI systems are capable of producing literary, artistic, and technical works with limited human involvement. This development raises questions about how traditional copyright concepts such as originality, authorship, and ownership should apply to AI-generated content. Existing copyright laws were not drafted with such technologies in mind, leading to uncertainty and gaps in legal regulation. This paper examines the issue of authorship and ownership in AI-generated works and considers whether current copyright frameworks are capable of addressing creations produced with the assistance of artificial intelligence. It analyses key questions surrounding AI-generated content, including whether artificial intelligence can be regarded as an author, whether copyright ownership should be granted to AI developers, and whether user-provided input or prompts amount to sufficient creative contribution. The paper argues that recognising artificial intelligence as an author is incompatible with the fundamental objectives of copyright law, which are designed to protect human creativity and expression. It further suggests that granting ownership where there is little or no human creative control may disturb the balance between encouraging innovation and safeguarding public interest. The analysis emphasises the need for a legal approach that takes into account different levels of human involvement in AI-assisted creation. The paper concludes that copyright law must evolve through carefully tailored frameworks that respond to technological change while continuing to maintain its human-centred foundation, particularly through clearer standards for human control, lawful training data, and limited statutory reform.
| 📄 Type | 🔍 Information |
|---|---|
| Research Paper | LawFoyer International Journal of Doctrinal Legal Research (LIJDLR), Volume 4, Issue 3, Page 401–413. |
| 🔗 Creative Commons | © Copyright |
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