Your Data, Their Wealth: The Price of Human Input to the AI Economy
James Felton Keith

political economy, digital economy, data unions, ownership, wealth distribution

Keith Institute

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In an AI-driven economy that profits from the hidden traces of ordinary life, a bold economist argues that everyday human behavior is productive labor—and that the public deserves ownership, bargaining power, and a share of the wealth it creates.
Most discourse surrounding artificial intelligence is fixated on the symptoms: privacy concerns, hallucinations, or existential safety risks. In Your Data, Their Wealth: The Price of Human Input to the AI Economy, James Felton Keith pivots from these tactical debates to the structural heart of the matter: political economy. Keith posits that we are living through a new enclosure movement, one where the raw materials of the modern economy are not land or oil, but the continuous, productive output of human life itself.
The book’s central strength lies in its relentless dismantling of the term “user.” Keith argues that by framing people as passive consumers of digital services, tech firms have effectively institutionalized a system that obscures our role as the primary producers of AI intelligence. Every search, click, correction, and cultural expression is not merely a byproduct of digital life; it is a vital input that improves systems, sharpens predictions, and drives profit. Keith replaces the hollow, thin concept of “data” with the richer, more visceral idea of “traces of life.” These traces—behavioral patterns, collective rhythms, and inferred preferences—are the assets that companies aggregate to consolidate power, reduce uncertainty, and eventually dominate markets.
Keith’s analysis of how these traces are converted into capital is sharp and sobering. He traces the legal and economic architecture that allows socially generated value to be privately enclosed, explaining how property, labor, and privacy laws have systematically left the public “blurry and undercounted.” By drawing on information theory and business metrics, he demonstrates that the low or non-existent “price” paid for our contributions is a result of structural power imbalances, not a reflection of low economic worth. When human behavior is digitized and scaled, it generates tangible gains in operating performance and investor valuation, yet the contributors remain locked out of the upside.
The final section of the book is where Your Data, Their Wealth shifts from a brilliant diagnosis to a manual for institutional redesign. Keith does not merely complain; he proposes a future built on multi-level ownership. He advocates for data unions, collective bargaining structures, and "Data Dividends" that would allow individuals to share in the wealth their participation creates. His argument is that if we are the engines of the AI economy, we deserve a seat at the table where the value is distributed.
This book is essential reading for policymakers, economists, and anyone who feels that the current digital status quo is fundamentally broken. It is a clarion call to stop treating AI extraction as a technical or ethical puzzle and to start treating it as a question of distributive justice. For those tired of watching the wealth of their daily lives be harvested without compensation, Keith provides something invaluable: a framework for seeing the hidden labor of our digital existence and a practical argument for why the next great labor fight will be about who owns the future of intelligence.





