Mandatory AI Revenue Sharing System Proposed in India

A government panel in India has suggested a mandatory framework requiring significant Artificial Intelligence (AI) enterprises, including global giants such as OpenAI and Google, to compensate content creators with a portion of revenue for training their AI systems. This initiative presents a considerable challenge to the existing data practices of major tech companies.

Access to Indian Content and Royalties

The panel, which was formed in April, has published a report recommending that AI companies should gain access to Indian content for their training purposes; however, they must contribute royalties to a centralised fund. This fund would advocate for copyright holders, ensuring that creators receive payments without having to manage the tracking of their work within extensive AI datasets.

Difference from the US Approach

This proposed model represents a significant deviation from the approach taken in the United States, where AI firms assert that utilizing publicly available content for training their models is classified as “fair use” and does not necessitate fees. The Indian panel explicitly dismissed the “opt-out” models found in areas like the European Union, arguing that placing the onus of tracking on individual creators is unjust and impractical.

Industry Opposition

The proposal has quickly faced resistance from major technology associations. Nasscom, a prominent tech industry body that includes members such as Google and Microsoft, has officially opposed the initiative, labelling the mandatory fee as a “tax or levy on innovation.” In contrast, content organisations like the Motion Picture Association have voiced a preference for licensing agreements over the implementation of new fees.

Feedback Period for the Public

The Indian government has allowed a 30-day window for the industry and the public to provide feedback and raise concerns before officials review the proposal. If approved, this system could establish a new global benchmark for AI regulation and alter the way that large language models obtain their data within one of the largest consumer markets worldwide.