Working Paper on AI and LLM

Working Paper on AI and LLM
  • Context:   

  • A committee constituted by the Department for Promotion of Industry and Internal Trade (DPIIT) has released a working paper titled "One Nation, One License, One Payment: Balancing AI Innovation and Copyright"

  • The paper addresses the conflict between AI developers needing data to train Large Language Models (LLMs) and content creators demanding compensation for the use of their copyrighted work. 

  • Key Recommendations: 

  • Mandatory Blanket License: 

  • The committee rejects voluntary licensing (individual deals) and proposes a mandatory statutory license. 

  • This grants AI developers the right to use any lawfully accessed copyrighted content for training without seeking individual permission from creators. 

  • In exchange, AI developers must pay royalties to rights holders. 

  • No Opt-Out Mechanism: 

  • Copyright owners cannot opt out or withhold their works from being used for AI training, provided the access is lawful. 

  • Institutional Framework: 

  • A new centralized body called the Copyright Royalties Collective for AI Training (CRCAT) is proposed to collect and distribute royalties. 

  • It will include copyright societies and collective management organizations (CMOs). 

  • Royalty Determination: 

  • Royalty rates will be fixed by a government-appointed committee (not market negotiation) and may be reviewed every 3 years. 

  • The paper suggests a flat rate or a percentage of the AI developer's gross global revenue. 

  • Retrospective Application:  

  • The obligation to pay royalties may apply retroactively to AI models that have already been trained on copyrighted data. 

  • NASSCOM's Dissent:  

  • The industry body for IT companies dissented, arguing that forced royalties act as a tax on innovation.  

  • They advocated for a Text and Data Mining (TDM) exception (allowing free use of publicly available data) or at least an opt-out mechanism for creators. 

  • There are fears that high royalty costs could create entry barriers for smaller AI start-ups compared to big tech giants.