Ellen Brown
May 26, 2026

Part 1 of this “Abundance Paradigm” series discussed predictions that artificial intelligence and robotics will in the relatively near future produce an economy of extraordinary abundance – one in which most labor is automated. The contention of Elon Musk is that this development will require some form of government-issued “Universal High Income” (UHI) to provide the consumer demand necessary to keep the economy functioning in a world where machines do most of the work.

Based on those projections, I argued that if a UHI were to become necessary, it could not realistically be financed through taxes or debt alone, but would require some form of debt-free sovereign money issuance — a modern version of Lincoln’s Greenbacks. The usual objection to government-issued money is that it would drive up prices and devalue the currency due to “too much money chasing too few goods.” But in this case, we would have too many goods and not enough money to provide the consumer demand to move them off the shelves. A source of abundant new money would actually be needed to keep trade flowing.

Objections came thick and fast. Some critics saw the AI revolution not as liberation but as a technocratic nightmare: AI surveillance, programmable digital money and “smart cities,” centralized control systems, and a future in which most people will own nothing while a tiny elite owns the machines, the data, and even the government. Others challenged the underlying premises: Would AI really generate such extraordinary abundance? Would productivity rise enough to justify something like a UHI? Or is this simply another round of Silicon Valley hype detached from economic reality?

Those are legitimate questions that deserve serious consideration, serious enough to require more than one sequel to address them. But whether or not we approve of Elon Musk, Sam Altman, or the AI industry itself, the AI revolution is already underway, driven by forces far larger than any individual actor. Businesses want AI because it lowers costs and increases productivity. Governments want it because they view it as strategically essential. Consumers increasingly rely on it because it saves time and improves convenience. The genie is out of the bottle.

Commentators say the AI boom is unlikely to disappear even if parts of it are overhyped. Investment firms, technology analysts, and economists increasingly describe AI not as a passing fad but as a foundational technological transition comparable to the invention of electricity or to the internet itself. Even skeptical analysts who question short-term productivity claims generally acknowledge that businesses are rapidly reorganizing around AI-assisted production.

The question now is not whether AI should exist but how we can adapt to it without falling into economic collapse or digital feudalism.

AI is Challenging the Fundamentals of the Capitalist Model.

For centuries, industrial economies have depended on a productive cycle based on work for pay. People work for wages, wages create consumer demand, and demand sustains production. But if machines increasingly perform not only factory labor but office and laboratory work — drafting contracts, diagnosing disease, designing products, writing software, driving vehicles, conducting research — then labor income will steadily decline even as productivity rises.

That creates a paradox for the capitalist model: Who buys the products if fewer and fewer people earn wages from producing them?

Historically, technological revolutions created new forms of employment even as they destroyed old ones. The automobile displaced blacksmiths but created mechanics, highway engineers, gas stations, motels, and suburbs. Computers eliminated typists but generated software industries and millions of office jobs. But AI is not confined to one sector. It is predicted to take jobs across the board.

We are not at that stage yet. But China, the world’s largest manufacturing power, is getting close, and Chinese commentators are beginning to grapple with the issue.

China as Forerunner and Test Case.

In a July 2025 opinion piece in the South China Morning Post titled “As AI Replaces Workers, China Could Consider Universal Basic Income,” Tech Editor Zhou Xin writes:

“In the past, Chinese officials have rejected proposals to distribute cash to households, even when many families were clearly in need of support. But while the term universal basic income has yet to appear in any official Chinese policy documents, it may become less foreign in the coming years because of the increasing replacement of entry-level jobs by machines.

Advances in technologies such as artificial intelligence (AI) and automation are expected to render many traditional labour roles obsolete ….

While new technologies will create new job opportunities, these roles are often unsuitable for workers displaced from traditional sectors. The pace at which old jobs are eliminated also outstrips the creation of new ones, which could lead to significant structural unemployment.”

A March 2026 article in ThinkChina raised a related issue. In “When AI Replaces Workers, Who Pays the Taxes?”, Chinese entrepreneur Simon Lin asks if AI systems and robots perform an increasing share of productive work, where will governments obtain tax revenue? Lin’s proposal is to tax the companies that profit from automation. That would help finance the government, but it doesn’t solve the distribution problem. Consumers still need purchasing power. Henry Ford understood this a century ago, when he said he needed to pay his workers enough to buy the cars they produced.

Another article in ThinkChina, titled “Socialism and Universal Basic Income: Creating Happy Societies in the Age of the Knowledge Economy,” addressed this issue in 2020. The article summary states:

“… [T]he knowledge economy offers great potential for bettering the lives of people. But capitalism may not be the best route to take. Power in the hands of a few, income gaps, job losses and wage cuts in the digital age bear this out. Can China offer a third way as it seeks to marry socialism with a market economy? The West is already considering some proposals with a socialist bent such as the Universal Basic Income (UBI). Surely, proponents of socialism can think of even more revolutionary ideas.”

The article continues:

“… China has a substantial low-income demographic. 600 million people live on about 1,000 RMB per month, which is insufficient even for housing rent alone. What we have here is inadequate demand from those with spending power, coupled with a tremendous surplus of production capacity.…”

The author observes that knowledge, once created, can be reused repeatedly at close-to-zero marginal cost, and that the AI-driven “knowledge economy” grows exponentially. That makes it possible for social productivity to grow exponentially as well, eliminating want and greatly enriching material and spiritual life. But capitalism poses some serious constraints on that promising future:

“… [A]s the knowledge economy becomes increasingly “smarter” (AI-driven), the share of wage income in the total distribution of income will continue to decline, while investment returns will be a constantly growing piece of the pie. This means the lion’s share of society’s wealth will be swallowed by capital. In the long run, only jobs with wages lower than the cost of automation have any chance of being kept.… This means that wage levels are bound to be kept low, even to the point of being inadequate for feeding oneself and one’s family.”

he article concludes: “China should kick-start preliminary research on universal basic income (UBI), as soon as possible. … What is UBI, after all, if not an attempt to rise above capitalism?”

Resource Constraints: Energy.

China may need to consider some sort of UBI, but in the United States the biggest practical hurdles to AI abundance may not be political but physical. Where will the U.S. find sufficient resources to produce the goods?

Critics point to the enormous energy consumption of AI data centers, the water demands of cooling systems, the mining requirements for batteries and semiconductors, and the environmental costs of rapid electrification. Some large data centers consume millions of gallons of water daily for cooling. Communities near rapidly expanding facilities have already reported stress on local water systems, and public pushback is growing.

Elon Musk has argued that the water problem is basically an energy problem, noting that once you have enough energy, desalination becomes cheap and simple. His proposed energy solution is solar. At a July 2017 National Association of Governors meeting, he said, “If you wanted to power the entire U.S. with solar panels, it would take a fairly small corner of Nevada or Texas or Utah; you only need about 100 miles by 100 miles of solar panels to power the entire United States. The batteries you need to store the energy, to make sure you have 24/7 power, is 1 mile by 1 mile. One square-mile. That’s it.” Not that all this equipment would need to be in one place, but that shows the projected scale.

The chief constraints to rapid and broad-scale solar development are political and regulatory. The solution being pursued now is solar collection in space, where the sun never sets, massive amounts of energy are available, cooling the equipment is not a problem, and there are no regulatory constraints.

Solar is not, however, the only possible energy solution. Advanced fission and fusion technologies are also in rapid development, largely due to AI-assisted engineering.

Small modular nuclear reactors (SMRs), once largely theoretical, are now moving into commercial development. SMRs are factory-built, standardized systems small enough in some cases to be transported by truck and assembled on site. Supporters argue that modular manufacturing could dramatically reduce both cost and construction time compared to conventional nuclear facilities.

Fusion energy, long mocked as perpetually “thirty years away,” is also advancing. Experimental reactors are already generating plasma temperatures hotter than the core of the sun, while major advances in magnetics are steadily improving stability. The main challenge is that superheated plasma behaves chaotically inside reactors, but AI systems are being used to predict these disruptions and make adjustments before they occur.

That doesn’t mean limitless energy is just around the corner. But the assumption that civilization is approaching an unavoidable energy ceiling may be outdated. In fact AI itself is becoming a key tool in creating the next generation of energy systems needed to support AI-driven productivity.

Physical Resources for Batteries, Electrical Grids and Agriculture.

AI is actually becoming a primary tool for solving resource problems in general. Modern AI-driven systems are dramatically improving electrical grid efficiency, agricultural productivity, recycling systems, and battery management. Precision agriculture reduces fertilizer and water use while significantly increasing yields. AI-managed electrical grids reduce wasted energy. Robotics improve mining precision and materials recovery. Advanced recycling systems increasingly recover rare earth minerals and lithium-ion battery materials that were once discarded as waste.

Thus while AI uses more power, the efficiency it creates in the rest of the physical economy may actually lead to a net reduction in total global resource consumption.

Solving the Water Crisis.

Singapore’s NEWater program is the gold standard for wastewater recycling, turning sewage into ultra-clean, drinkable water. It has now successfully “closed the water loop,” making the island nation resilient against external water shocks.

AI data centers are also now pivoting away from evaporative cooling to water recycling. Modern “closed-loop chilling systems” allow data centers to operate with near-zero direct water consumption once the system is filled. New major projects are marketing themselves as “water-neutral” by using closed-loop cooling technology that recirculates water rather than evaporating it in cooling towers.

Some analysts argue that the location of data centers is wrong. Unused areas are available that have abundant water supplies, existing industrial zoning, and underutilized energy infrastructure. But for communities already under stress from data centers that probably aren’t going anywhere, my own proposal would be to drill for primary (juvenile) water for residential needs. Continuously generated deep in the earth and rising through faults, primary water offers a clean, renewable, locally tappable water source independent of the surface cycle, easily accessible with robotic drilling and abundant energy. The model has been proven primarily in Africa. See my earlier article here.

Wind Power.

Meanwhile, China has successfully launched the world’s first commercial underwater data center powered directly by offshore wind. The Shanghai project was completed for less than half the cost of an equivalent 24-megawatt land-based facility, and by using seawater for cooling, it is about 30% more efficient and cuts electricity consumption by over 22%.

However, underwater data centers were not pioneered by the Chinese. Microsoft’s Project Natick, a 2018–2020 trial off the coast of Scotland, was a technically successful test that demonstrated higher reliability and lower failure rates than land servers. But Microsoft announced it was abandoning the project in mid-2024.

In the U.S., a private company like Microsoft must negotiate with local utilities and typically must pay for its own grid upgrades, which can add years and millions of dollars to a project. In China, state-owned power companies provide special energy pricing and dedicated high-voltage lines for data center clusters. There are also regulatory hurdles in the U.S. and Europe, where complying with environmental regulations is a slow and costly process.

In China, by contrast, the government designates specific areas where environmental reviews and construction permits are fast-tracked specifically for “Green AI” projects. As a result, construction is often 30% to 50% faster than for their Western counterparts. The Chinese underwater data centers are part of a massive state-led industrial policy called the “East-to-West Computing Resource Transfer,” a highly coordinated top-down strategy that treats data centers as a critical national utility integrated directly into the national energy grid. Besides providing direct subsidies and grants, the Chinese government has built offshore wind farms specifically designed to plug into data center units. Placing the AI servers directly at the base of the wind turbines eliminates the energy loss and cost of transmitting power back to the shore.

This is another real-world example demonstrating the need for public investment in infrastructure, ideally through a national infrastructure bank, to fund projects that private markets find too risky or too expensive to build alone.

The Road to Creative Freedom or to Digital Feudalism?

The potential for AI/robotic productivity is promising, but it will not automatically benefit the public. Productivity has already risen dramatically over the past century, while wealth has concentrated at the top.

The future emerging around AI contains two radically different possibilities. One is a highly centralized technocratic system in which wealth and power become highly concentrated, while citizens are managed through digital currencies, surveillance, and algorithmic governance. The other is a civilization in which automation gradually liberates human beings from monotonous labor, shortens work time, expands access to education and creativity, and allows technological abundance to serve broad human flourishing rather than narrow financial interests.

Both futures are technologically possible. Which one emerges will be determined not by the machines themselves but by the political and monetary systems governing them.

Part 3 will examine what is probably the most emotionally charged issue involved in the AI revolution: digital money, central bank digital currencies, surveillance fears, and whether an AI-driven economy inevitably leads to a programmable financial control grid.

Be sure to check Ellen Brown’s earlier posts here on the AI Abundance Paradigm.

Originally published on ScheerPost.com.

Shared via Creative Commons.

Ellen Brown ScheerPost.
MAY 10, 2026

A Universal Basic Income (UBI) has long been proposed as a way to cushion the blow of jobs lost to automation. Under that model, everyone receives a modest monthly payment – enough to cover basic needs and prevent extreme poverty.

But Elon Musk has gone further. On April 16, he posted on X:

“Universal HIGH INCOME via checks issued by the Federal government is the best way to
deal with unemployment caused by AI.

“AI/robotics will produce goods & services far in excess of the increase in the money
supply, so there will not be inflation.”

Rather than a subsistence stipend, Universal High Income (UHI) would be a level of income allowing ordinary people to live well in a world where machines do most of the work. Musk has also said that AI and robotics are the only things that can solve the massive U.S. debt crisis.

That sounds promising, but where will the government get the money to pay the UHI? Critics say any government that tried it would go bankrupt. There are also other concerns, which will be addressed in Part 2 of this article. Here we will look at the financial underpinnings: why UHI is even thinkable, why AI forces a reexamination of how money enters the economy, why the current system cannot scale to meet what is coming, and the implicit transition needed to meet that challenge.

Why the Current Money System Cannot Scale.

The national debt of the U.S. government just topped $39 trillion. China’s is $18.7 trillion. Japan’s is $8.6 trillion. Those of the UK, France, Germany, Italy and Spain are each in the multi-trillion-dollar range. Collective global debt now stands at $353 trillion, 305% of the world’s annual economic output. So even if, hypothetically, everything produced in the world in a year were applied toward liquidating the debt, it still would not be enough to pay it all off.

In fact the debt can never be repaid, because of the way money currently enters the system. Nearly all of the money supply today is created by banks when they make loans. Banks do not lend their existing capital. The loan itself creates the money. The bank adds the loan amount to the asset side of its balance sheet and balances that sum with the same amount on the liability side. When the borrower withdraws or transfers the funds, either the bank takes them from its reserves in “vault cash” or the Federal Reserve debits the bank’s digital reserve account at the central bank. But the lending bank typically has funds coming into its reserve account at about the same rate as they are going out, so its reserves are continually replenished. Thus a very small reserve account can support a much larger money creation engine. For decades before the Fed discontinued the reserve requirement in 2020, it hovered at around 10%.

The chief problem with this debt-based system is the interest, which the bank does not create in its original loan. For a typical long-term loan, interest can double the total tab or more. Where is the money to come from to pay this added liability? Across the system as a whole, it must either come from more borrowing or from existing funds. In the case of governments, that means issuing interest-bearing bonds or tapping taxes and other revenues. The interest on the debt compounds, meaning the government is paying interest on interest. This makes the debt increase exponentially, until it is mathematically unsustainable. Then bankruptcies occur, of banks or even whole governments. Booms turn into busts, and the cycle begins again.

Today, interest on the federal debt is the second largest budget line item after Social Security, exceeding $1 trillion. Meanwhile, workers are losing jobs to AI/robotics, shrinking the income tax base. The system is clearly unsustainable.

How to Raise Demand to Scale to the Upcoming Supply.

A Universal High Income would replenish the shrinking tax base by replacing the lost wages of unemployed workers. But where will the money come from to pay the UHI? The only sustainable solution is for the government to issue it interest-free. That does not mean through the Federal Reserve, which creates money in the same way banks do: it buys federal interest-bearing securities with accounting entries. The Fed collects the interest, which it is supposed to return to the Treasury after deducting its costs. But since 2008, its costs include paying interest on the reserves of its participating  banks, which consumes its profits. (See my earlier article here.)

The only interest-free, debt-free solution that will actually increase the money supply sufficiently to match the projected productivity of AI/robotics is for the money to be issued directly by the Treasury.

This is not a radical new idea. It is authorized in the U.S. Constitution, which provides in Article 1, Sec. 8, that “The Congress shall have Power To … coin Money [and] regulate the Value thereof .…” Abraham Lincoln used government-issued “Greenbacks” to avoid a crippling debt to British-backed bankers. Debt-free government-issued money was also the funding mechanism by which the American colonists succeeded in creating a thriving economy and liberating themselves from the oppressive yoke of the British Empire.

In his 1729 pamphlet “A Modest Enquiry into the Nature and Necessity of a Paper-Currency,” Benjamin Franklin argued that a lack of currency was a tax on industrious farmers and producers, and that a reliable, locally issued paper currency was the “oil” for the gears of trade. The “Nature and Necessity” of this currency was to facilitate the movement of goods between neighbors. Franklin observed that the British strategy of keeping the colonies short of cash was a method of economic suppression. By forcing the colonies to use gold and silver, which were constantly drained back to London to pay for imports, the Crown kept the colonies in a state of permanent debt and low productivity. When the money supply matched the productive capacity of the people, universal prosperity resulted without inflation.

This logic evolved into the “American System of Political Economy” championed by Henry Carey, economic advisor to Abraham Lincoln. He wrote:

“Two systems are before the world… One looks to pauperism, ignorance, depopulation, and barbarism; the other in increasing wealth, comfort, intelligence, combination of action, and civilization. … One is the English system; the other we may be proud to call the American system, for it is the only one ever devised the tendency of which was that of elevating while equalizing the condition of man throughout the world.”

In the context of the 21st century, the “oil” that best lowers the friction of trade is debt-free government-issued money similar to Lincoln’s Greenbacks and colonial scrip. Rather than implementing a radical financial innovation, we would be returning to our roots.

Inflation or Deflation?

The chief objection to the colonies’ paper “scrip” was that they tended to over-print, so that “demand” (money) outstripped supply. Too much money chasing too few goods produced price inflation. But in the 21^st century, we will soon have the opposite problem: too little money chasing too many goods. Machines don’t need food, clothing, shelter, transportation, medical treatment or other services. So who will buy those goods and services?

Money needs to be issued to human consumers, and not just to a few wealthy human consumers serving as debt brokers thriving on interest. To create sufficient demand for the voluminous output of AI/robotics, it needs to go to the whole national population, evenly distributed. Not only can UHI work in that sort of abundant supply without producing price inflation; it is actually essential to prevent deflation.

In a conversation on X, Musk wrote:

“In a normal economy, issuing more money simply increases the dollar price of the existing output of goods & services, meaning people do NOT get more stuff. If AI/robotics massively increase goods & services output, then you actually MUST issue dollars to people or there will be massive disinflation. “

As paraphrased on Yahoo Finance (reposted from Benzinga), Musk wrote that handing out more dollars becomes a problem only when the economy’s supply of goods and services fails to surge alongside the money supply. His claim is that AI and robotics could lift production so sharply that the bigger risk would be falling prices, not rising ones.

But aren’t falling prices a good thing? In this case, no. Prices would be falling due to a lack of demand, meaning producers can’t find customers for their products. They wind up laying off workers and eventually going bankrupt. When spread across the whole economy, the result is a deflationary spiral: prices fall, businesses lose revenue, and the economy contracts, not because production is inadequate but because purchasing power is insufficient. The result is recession or depression. In the Great Depression of the 1930s, food was rotting in the fields while people were starving, because they were out of work and had no money to spend.

Job cuts from AI are already happening. According to the same Benzinga article:

“Evidence of near-term strain is showing up in corporate announcements: employers disclosed more than 27,000 job cuts linked to AI in the first quarter of 2026, according to Challenger, Gray & Christmas. The outplacement firm said that figure was up 40% from the same period a year earlier. “

Robert Reich reports that wages are around two-thirds of the typical corporation’s total cost, and that in the first four months of 2026, big U.S. corporations cut over 128,000 jobs.

How Soon Will All This Happen?

Another Benzinga article, reposted on Yahoo Finance on March 16, detailed Musk’s projected time frame:

Speaking remotely to the Abundance Summit last week, Musk told XPRIZE founder Peter Diamandis that the global economy is on the verge of an explosion so massive it defies historical precedent.

“I’d say the economy is 10 times its current size in 10 years,” Musk said, before quickly clarifying that the growth could be even more explosive. “Greater than,” he added, framing the projected shift in economic output as a “fairly comfortable prediction.” … “Obviously if there’s like World War III or something, that could put a kink in those plans or those expectations,” Musk warned. “But in the absence of World War III, if current trends continue, I would say the economy 10xes in 10 years.” … The catalyst for this vertical climb isn’t traditional manufacturing or trade, but the “hard takeoff” of artificial intelligence. Musk explained that civilization is currently moving through a period of recursive self-improvement, where AI models are increasingly being used to design and build their successors.”

Ray Kurzweil, author of The Singularity Is Near, sees AI reaching Artificial General Intelligence (human-level intelligence across virtually all domains) by 2029, and full transformative abundance by 2045.

Other experts question these time projections, but a radical transformation of traditional manufacturing and trade is likely to happen sometime in the reasonably near future. The question is, will the money system transition soon enough to rescue all the laid-off workers from homelessness and famine?

The Sovereign Wealth Fund Alternative.

There is another model for distributing the gains of automation, one that can be phased in gradually as the AI workforce expands. It comes from Sam Altman, CEO of OpenAI. In an ironic twist, Altman and Musk, who jointly founded OpenAI in 2015, are now locked in a high-profile legal battle over whether Altman diverted Musk’s $44 million investment to transform what was conceived as a nonprofit “for the benefit of humanity” into a highly lucrative for-profit enterprise.

That dispute aside, Altman’s alternative model for sharing AI-generated wealth is a national sovereign wealth fund seeded by the profits of AI and robotics. His proposed American Equity Fund would take public stakes in the companies and technologies driving automation, capture a portion of the resulting productivity gains, and distribute them as universal dividends. The Fund would not replace a Universal High Income but would complement it.

This approach has several advantages. It ties payments directly to real output, scales automatically with productivity, and can be introduced gradually, avoiding the shock of issuing large payments before the supply side has fully expanded. It would resemble the Alaska Permanent Fund, which distributes oil revenues to residents, except that here the resource would be the most powerful general-purpose technology since electricity.

Conclusion: A New Monetary Logic for a New Productive Era.

For centuries, money has been issued as a claim against the future productivity of human labor, repaid from the income that labor generates. The logic of this debt-based system collapses when machines become the primary producers of goods and services. Then the limiting factor becomes purchasing power — the ability of human beings to access the abundance their own technologies create. That requires a monetary architecture that expands with output rather than debt, and distributes income not through wages alone but through mechanisms tied to the productive capacity of the whole system.

Universal High Income and a sovereign wealth fund are two ways of doing that. One ensures a stable floor of demand; the other ensures that the public shares in the gains of automation. Both would be grounded in real production. But for the public to have access to those gains, the money supply needs to expand in proportion to the expanding pool of goods and services. This can be done by restoring the innovation our forefathers baked into the Constitution: debt-free money issued by the government itself.

How to fund a UHI without triggering inflation or driving the government into bankruptcy is the first objection critics raise, but there are others. They argue that people would stop working or stop learning, that society would collapse into idleness or chaos, that life would lose meaning without jobs, that the government would have the power to control how people spend their money.  Will a UHI ring in the promised utopia or lock us into a state-controlled digital prison? Part 2 of this article will address those concerns.

Be sure to check Ellen Brown’s earlier posts here on the AI Abundance Paradigm.

First published on Scheerpost.com

Shared via Creative Commons.