Yaniv Benhamou calls for new institutions to ensure that the people whose knowledge trains AI models share in the returns.
Millions of users generate trillions of tokens training LLMs without compensation; collective data governance must enforce access rights and profit-sharing. Incoming data ownership regulation will reshape AI sourcing costs, vendor agreements, and corporate compliance strategies.
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Innovation
Aug 11, 2026
Yaniv Benhamou
Millions of people continuously generate the raw material on which AI is trained, yet almost none shares in the wealth it creates. This underscores the need for data cooperatives representing internet users, creators, and other rights holders to negotiate access to the content being fed to large language models.
Yaniv Benhamou calls for new institutions to ensure that the people whose knowledge trains AI models share in the returns.
Millions of people continuously generate the raw material on which AI is trained, yet almost none shares in the wealth it creates.
Frontier AI models are trained on the accumulated digital output of humanity, which AI companies acquired essentially for free.…
Mozilla Data Collective seeks to build AI's data economy around trust - SiliconANGLE
The objective is not to use the fewest tokens. It is to extract the highest return from every unit of intelligence consumed.
The AI revolution will not be that destructive, Sorrell says, but huge efficiency gains are coming.
