AI–copyright Overhaul with ‘One Nation, One Licence, One Payment’ Model

Syllabus: GS2/Governance; GS3/Artificial Intelligence

Context

• The DPIIT-led committee has released a working paper titled ‘One Nation, One License, One Payment: Balancing AI Innovation and Copyright’.

About

• The DPIIT-led committee has recommended a “hybrid model” of compensation for use of copyrighted content in AI training.
• If implemented, India would become the only country to prescribe a statutory licensing regime for AI developers, with royalty rates prescribed by a government-appointed committee.

Its Key Features

• Aim: To protect the rights of IP holders (by having a compensatory model) and at the same time ensuring mandatory licensed access to quality datasets for AI developers.
• Mandatory Blanket Licence: All AI developers will be required to obtain a statutory blanket licence to use all lawfully accessed copyright-protected works for training AI systems.
• Statutory Remuneration Right for Creators: Creators and copyright holders will receive royalties mandated by law, instead of individually negotiated licensing deals.
• Creation of CRCAT (Copyright Royalties Collective for AI Training): A new umbrella body designated under the Copyright Act, 1957 will:
  • Collect royalties from AI developers.
  • Distribute them among classes of copyright holders.
  • Act as a centralised facilitator for the blanket licence.
• The Centre will constitute a committee to determine the royalty rate. 
  • It will consist of senior government officers, senior legal experts, financial or economic experts, and technical experts with expertise in emerging technologies. 
  • A CRCAT member from and AI developers’ representative will also be part of the committee.
• Royalty Rates: The panel will set royalty rates, while ensuring that they are fair, predictable, and transparent.
  • It will also review and adjust rates every 3 years, to reflect technological and market developments.
• Legal Relief: The rates set by the rate setting committee may be challenged before the court and would be subject to judicial review.
• Rejection of Voluntary Licensing: The committee rejects private, voluntary licensing agreements (e.g., OpenAI–AP deal) due to:
  • High transaction costs,
  • Unequal bargaining power,
  • Risk of big companies monopolising licensing,
  • Inadequate access to diverse training data.
• Prerequisite of Lawful Access: AI companies cannot bypass paywalls or technological protection measures using the mandatory licence. They must have lawful access to data.
• Retroactive Payments: It suggests retroactive payment of royalties in cases where copyrighted data has already been ingested into AI systems and also lays a framework for establishing burden of proof in related lawsuits.

Need for Such Model

• Infringement of Copyright Act: The AI training involves multiple acts of reproduction from downloading and storing works to generating temporary copies that raise clear infringement questions under India’s Copyright Act.
• Compensation to Copyright Holders: AI companies have non-discriminatory access to copyrighted work, there is a need that all copyright holders are compensated in an equitable way. 
• Growing Scepticism: It comes amid growing scepticism of news publishers in several jurisdictions over concerns of copyrighted material being used for training foundational models, without permission or payment. 
• Court Cases: Infringement has led to court cases where publishers have mounted a legal challenge against OpenAI over the unlawful utilisation of copyrighted material.
• Commercialised Use by AI Developers: Many AI Developers have built AI Systems which are commercially successful and generate huge revenues.
  • In order to ensure fairness and accountability, such AI Developers must be required to pay royalties to copyright owners for past usage of their works. 

Concerns Raised by Industry

• Concerns are being raised over the royalty rates fixed by a government-appointed panel.
  • Companies argue that they should be allowed to discuss mutually beneficial licensing rates among themselves.
• It could lead to slowdown in AI development which ultimately harms India’s ambitions to build and scale indigenous AI capabilities.
• The implementation must be fair and scale-dependent; otherwise, it risks becoming an entry barrier for startups and further strengthening incumbents.

Conclusion

• It comes in the wake of soaring AI adoption, mushrooming AI startups and conflicts over the use of copyrighted content by AI developers.
• The government argues that a licensing framework allows domestic AI firms access to rich, copyright-protected datasets, reduces barriers to innovation and aligns with India’s broader goal of building sovereign AI capabilities.

Source: IE