Copyright Challenges in Training Large AI Models

Artificial Intelligence (AI) has evolved rapidly in the past decade, and one of its most powerful applications is the development of large AI models. These models, often built using machine learning and deep learning, rely on vast amounts of data to function effectively. 

However, when this data includes copyrighted material, it raises significant legal and ethical challenges. In India, copyright law is governed by the Copyright Act, 1957, and the interpretation of this law in the context of AI remains complex.

This article explores the copyright challenges in training large AI models, with a focus on Indian law, international developments, and the need for clearer legal frameworks.

Understanding Large AI Models

Large AI models such as generative AI systems, natural language models, and image recognition tools are trained on massive datasets. These datasets often include:

• Books, articles, and journals.
• Images, videos, and music.
• Online content from websites and social media.

The core issue is that much of this training data is protected under copyright law. AI companies argue that the use of this data is transformative and falls under exceptions like fair dealing, while creators worry that their work is being exploited without permission or compensation.

Copyright Basics under Indian Law

Under the Copyright Act, 1957, copyright protects original literary, artistic, musical, and dramatic works, as well as films and sound recordings. Copyright gives the owner the exclusive right to:

• Reproduce the work.
• Issue copies to the public.
• Perform or communicate the work publicly.
• Adapt or translate the work.

In India, copyright generally lasts for the lifetime of the author plus 60 years. Any use of a copyrighted work without permission may amount to infringement, unless it falls within exceptions such as fair dealing (Sections 52 of the Act).

The main challenge with AI training is determining whether the copying of data for training purposes amounts to infringement or falls within permissible exceptions.

Key Copyright Challenges in Training AI

Reproduction of Works

AI developers often copy entire books, datasets, or images to train models. Even if the final AI output is not identical to the original, the training process itself involves reproduction of works. Under Indian law, this is a restricted act unless covered by an exception or licensed use.

Fair Dealing and Research Exceptions

Section 52 of the Copyright Act allows limited use of works for purposes such as private research, criticism, or review. However, whether training AI qualifies as “research” is debatable. The purpose is usually commercial, not private or academic. Courts in India have not yet clarified whether mass data scraping for AI falls within fair dealing.

Derivative Works and Originality

When AI generates new content based on training data, is it creating a derivative work of the original copyrighted material? For example, if an AI trained on thousands of Bollywood scripts generates a new screenplay, can it be considered an infringing derivative work? Indian law has no clear guidance on this point.

Moral Rights of Authors

Authors have moral rights under Section 57 of the Copyright Act, including the right to attribution and the right against distortion of their work. If AI systems generate content that mimics or distorts the style of a specific author, it could raise questions about moral rights violations.

Database Protection

Large AI models often rely on databases compiled by third parties. While India does not provide sui generis database protection like the EU, the selection and arrangement of a database can still be protected under copyright if it reflects originality. Using such databases without permission could raise infringement claims.

International Developments on Copyright Challenges in Training Large AI Models

Globally, courts and regulators are grappling with similar issues:

• United States: Courts are examining whether AI training can be considered “fair use“. Several lawsuits have been filed against companies like OpenAI and Stability AI for allegedly misusing copyrighted data.
• European Union: The EU’s Copyright Directive provides a framework for text and data mining, allowing certain uses unless expressly prohibited by rights holders.
• United Kingdom: The UK has considered expanding copyright exceptions for AI training, but the proposal faced resistance from creative industries.

These developments indicate that India too will need to evolve its copyright framework to address AI training challenges.

Copyright Challenges in Training Large AI Models in India

Lack of Specific Provisions

The Indian Copyright Act does not specifically address AI or machine learning. This creates uncertainty for both AI companies and copyright owners. Courts may have to rely on broad interpretations of existing provisions, which could lead to inconsistent outcomes.

Judicial Approach

Indian courts have generally taken a balanced approach between protecting rights holders and promoting public interest. For instance, in cases involving photocopying for educational purposes, courts have emphasised access to knowledge. A similar debate may arise for AI training—whether it serves public interest or unfairly exploits creators.

Possible Policy Responses

• Introducing explicit text and data mining exceptions, similar to the EU model.
• Creating a compulsory licensing system, where AI companies pay fees for using copyrighted works.
• Establishing a collective management mechanism, where rights holders receive royalties through copyright societies.

Ethical and Economic Dimensions

Apart from legal concerns, there are ethical and economic implications:

• Loss of revenue for creators: Authors, musicians, and artists may lose potential earnings if their works are used without permission.
• Transparency issues: AI developers often do not disclose the sources of training data, making it hard to identify infringements.
• Market imbalance: Large tech companies with access to data benefit, while individual creators may be sidelined.

Balancing innovation with fair compensation for creators is a key challenge.

Conclusion

The training of large AI models raises complex copyright challenges in India and worldwide. While AI has the potential to transform industries, it cannot thrive in a legal vacuum. India’s Copyright Act, 1957, was not designed with AI in mind, and therefore struggles to provide clear answers to issues like reproduction, derivative works, and fair dealing.

Moving forward, India must adopt a balanced approach—protecting the rights of creators while encouraging innovation. Clearer laws, fair licensing systems, and judicial clarity can ensure that AI development remains both legally sound and ethically fair.