The Intersection of Machine Learning and Indian Copyright Jurisprudence: The Case for a Dedicated Artificial Intelligence Content Statute

The exponential rise of generative artificial intelligence (AI) has profoundly disrupted established legal doctrines surrounding intellectual property, posing complex challenges for global copyright regimes. In the Indian context, the interaction between generative models and the Copyright Act of 1957 has introduced deep regulatory uncertainties, particularly regarding uncompensated web-scraping for algorithmic training and the ambiguous legal standing of machine-authored content. Although India has built a robust framework for digital governance and technological scaling, its current statutory protections remain heavily skewed toward network security and data privacy, leaving intellectual property safeguards severely neglected. This paper provides a granular evaluation of how AI models strain existing Indian copyright laws and explains why iterative, piecemeal statutory revisions are fundamentally insufficient. To address these systemic gaps, this research advocates for a standalone legislative enactment specifically engineered to handle content regulations at the intersection of AI and copyright. By introducing mandatory dataset logging, creating a distinct legal tier for synthetic works, and optimizing automated text and data mining (TDM) licensing models, this proposed framework balances the rights of human creators with the societal need for computational innovation.