The AI Dividend: Turning Computational Power into Shared Prosperity
How to fund The AI Dividend from the engine of automation itself: make cloud computing a public utility, set prices above raw computational cost, & channel the difference into universal basic income.
As the artificial intelligence revolution barrels forward, Silicon Valley is abuzz with a mix of anticipation and alarm. We’re entering an era that promises unprecedented prosperity but also presents the most profound economic challenge since the Industrial Revolution: the devaluation of human labor as it competes with computational labor—AI systems capable of performing complex tasks once considered the exclusive domain of people. With a staggering 60% of jobs in advanced economies exposed to AI’s disruption, we risk creating a permanent rentier class that owns the “means of computation,” while the rest of us are left behind.
This moment demands a new social contract—a mechanism that doesn't just soften the blow of automation, but actively democratizes its gains. The centerpiece of this new contract should be: The AI Dividend.
The AI Dividend is a proposal to fund a Universal Basic Income (UBI) by treating the foundational layer of the AI economy—mass-scale computational infrastructure—as a public owned utility. It is a plan to create a self-funding dividend for every citizen, paid for directly by the engine of the automation economy itself. The productivity gains from the powerful AI systems represent a public inheritance built on centuries of human ingenuity. This isn't a handout; it's a rightful return. The AI Dividend is how we claim it.
The Mechanism: A Public Computational Trust
The logic starts with the fuel of the revolution: computation. Cloud computing has seen exponential growth, driven by the intense demands of AI platforms. By recognizing computation as the backbone of AI, we can leverage it as a policy instrument for our collective benefit.
Imagine a scenario where a public body, a Public Computational Trust, operates foundational cloud infrastructure, much like we manage other essential public resources. Inspired by our central banking system, a regulatory arm of this trust could set the price of computation much like the Federal Reserve sets interest rates.
The objective of a computational reserve would be to manage the pace of the AI transition, ensuring economic stability and shared prosperity. It would achieve this through a powerful dual-purpose mechanism.
First, in times of rapid job displacement, the Reserve could raise the price of computation. This acts as a brake on automation, making human workers more competitive and ensuring AI is adopted for its genuine productivity gains, not just because it is marginally cheaper.
Second, this price is set above the raw cost of processing power, and the difference is captured as public revenue. Therefore, raising the price not only moderates the pace of disruption but also increases the amount of money flowing into The AI Dividend fund, providing more support to citizens when they need it most.
This creates an elegant, self-regulating feedback loop where the very engine of disruption becomes the source of economic security.
A Blueprint for Progress
While an AI Dividend may seem far-fetched, history shows that transformative policy shifts often arise from necessity. Like the Industrial Revolution, this upheaval challenges our socio-economic fabric. Past societies navigated such transitions by creating new institutions: labor unions and welfare states arose to mitigate the inequities of industrialization, while financial crises birthed central banks. We stand at a similar crossroads.
The New Deal overhauled government to combat the Great Depression's unemployment crisis. More recently, the COVID-19 pandemic spurred massive government intervention, including temporary basic income measures. If dire predictions of AI-driven job displacement prove accurate, the public will demand similarly ambitious reforms.
We also have modern models. Just as oil-rich nations like Norway use natural resources to fund social programs, we can harness the defining resource of the 21st century—computation—for the public good. Rather than tapping oil reserves to fund annual payouts, as Alaska has done, we would derive revenue from the infrastructure powering the AI revolution.
The shift toward public control of AI infrastructure is already happening. The U.S. just announced Stargate, a $500 billion public-private AI infrastructure investment, while China has deployed over $138 billion since 2017 to build state-controlled data centers. Both superpowers now treat computational capacity like critical national infrastructure too important for pure market control.
If this vision seems radical, note that OpenAI's Sam Altman has called for similarly transformative approaches arguing that AI will force us to completely reconfigure our social contract.
Critics will argue that public ownership stifles innovation. But the opposite is true. Industry experts have long argued that cloud computing, like water or electricity, should be a public utility. The regulation of electricity did not stifle innovation in the countless devices that use it; a public cloud can provide a stable, accessible infrastructure that fosters more innovation atop it.
The political obstacles are real: entrenched tech oligopolies with unprecedented lobbying power, the complexity of coordinating across jurisdictions, the risk of capital flight, and legitimate concerns about government efficiency in managing cutting-edge infrastructure. Yet these same firms now accept public investment through projects like Stargate, setting precedents for public-private coordination.
Crises and disruption drive previously unthinkable policies. If mass unemployment arrives, today's political impossibility becomes tomorrow's necessity. Our task is to have frameworks ready when that window opens.
A Pragmatic, Self-Sustaining Model
This proposal stands out for its self-sustaining design. Rather than rely solely on taxation to fund a UBI for those displaced by automation, The AI Dividend is funded by a revenue stream directly tied to AI's economic impact. As the force automating jobs also funds the solution, incentives are aligned. This creates a sustainable income source independent of an employed labor force that businesses may no longer require, making it a more viable and balanced approach than tax-funded models that would rely on a wealthy elite to support a population whose labor they no longer need.
This vision does not spell doom for our livelihoods. Instead, it offers a new social contract where each of us has a stake in technological advancement. The promise of automation has always been for us to work less without sacrificing our standard of living. Let’s chart a course into the future that promises not displacement, but a shared prosperity in which we all have a claim.
The proposal outlined here, The AI Dividend, is the public introduction to a multi-year project dedicated to designing a new social contract for the AI age. Behind this vision lies extensive work on the underlying economic model and pricing mechanisms, the technical architecture of a public cloud , and the political coalitions needed to make it a reality. We are at a hinge point in history, with a choice between two futures. I believe the path to a more humane and prosperous world is not only possible but within our grasp, and I look forward to sharing more of this work in the near future.
Good to explore creatively. And, I think a more fitting label is that you propose to *extend*, to further socialization of IT infrastructure. Recognize what's *already* socialized, as military and spy machinery for U.S. national-state primacy (Farrell and Newman 2023, https://bit.ly/FarNew-2023 ).
And you err in blurring Norway's sovereign wealth fund from fossil fuels. Not true, what you wrote here:
"We also have modern models. Just as oil-rich nations like Norway use natural resources to fund social programs, we can harness the defining resource of the 21st century—computation—for the public good."
Nordic populations have been typically hostile to UBI. For example 71% of Swedes opposed, in 2020, a hypothetical proposal to start a UBI: see the analysis by sociologist Max Koch (2021: 7, https://bit.ly/KochMa-2021 ). Nordic welfare states don't run on unconditional transfers to adults able to work, notwithstanding Finland's much-discussed, localized pilot parallel that came to a draw. Bo Rothstein's 2017 Social Europe brief against UBI from his expertise in Nordic welfare policy developments, is lucid. ( https://bit.ly/RothB-2017 ). For a wider-ranging roundup with eyes on the USA. see sociologist Jeff Manza in Theory and Society, 2023 ( https://bit.ly/ManzaJ-2023_TS ).
You also err in suggesting that computation is "the defining resource of the 21st century" as contrasted with oil and such fuels. That's false. These systems run hard on fossil fuels, rare earths, freshwater, and major land use changes destructive of biophysical resources. For a start on that, see Chu (2024, https://on.ft.com/4chyMNI) and Gupta, Bosch, and van Vilet (2024, https://bit.ly/GuBovV-2024-3_21 ).
I also just became a paid annual subscriber. Great and innovative article.