Forward Economics
Chapter 18
Artificial Intelligence and the Forward Economy
The Greatest Prize in Human History
Something extraordinary is happening.
For the first time in human history, we are building machines that think. Not merely calculate — think. Machines that write, reason, diagnose, design, teach, discover, and create. Machines that do not tire, do not ask for raises, and do not need a pension.
The productivity implications are staggering. Conservative estimates suggest artificial intelligence will add $15 to $20 trillion to the global economy within a generation. Others put the number far higher. Some believe we are approaching a moment where AI systems begin accelerating their own improvement — a compounding of machine intelligence that makes every previous technological revolution look modest by comparison.
This is not science fiction. It is happening now, in data centers across America, at a pace that is quietly outrunning our ability to govern it.
The question before us — the question that will define the next century — is not whether AI will create extraordinary wealth. It will.
The question is: who will it belong to?
An American Problem
Before we answer that question, let us name what is actually at stake.
America was not founded on a philosophy of extraction. It was founded on the radical proposition that the purpose of a well-designed system is to secure the conditions under which all people can flourish — not merely the people who arrived first, or inherited the most, or moved fastest to claim the prize.
America’s Founders were not naive. They understood human nature with clear eyes. They knew that self-interest, left ungoverned, would consume any institution it touched. That is precisely why they built a constitutional architecture designed not to eliminate self-interest but to channel it — to create a system in which the pursuit of individual gain, properly structured, produced collective benefit rather than collective harm.
They called it a republic. They spent years arguing about how to design it. They were deadly serious about getting the architecture right — because they understood, from hard experience, that the architecture was everything.
We face the same design challenge today. Not in government, but in the economic institutions that increasingly shape the majority of conditions of American life — and none more consequentially than the institutions being built right now around artificial intelligence.
If we get this right, AI will be the most powerful engine of shared prosperity in human history. It will lift wages, broaden opportunity, reduce the cost of healthcare and education and energy, and unleash a wave of innovation that makes the digital revolution look like a warm-up act.
If we get it wrong, AI will be the most efficient engine of extraction ever built — a machine for concentrating wealth and power at a speed and scale that no previous technology has made possible.
The choice is ours. But it will not remain ours for long.
We Have Seen This Movie Before
In the mid-nineteenth century, a similar question was asked about the industrial economy.
The steam engine, the railroad, the telegraph — these were civilizational transformations. They multiplied the productive power of human labor by factors that would have seemed miraculous to prior generations.
The wealth created was real and enormous.
But the rules governing who captured that wealth were written quickly, in the interests of those who already had capital, and locked in before most people understood what was happening. By the time the consequences became visible — the Gilded Age, the robber barons, the grinding poverty amid spectacular plenty — the architecture was set. The rules had hardened into law, into custom, into the unquestioned assumption that this was simply how things worked.
American has spent the next 150 years managing the consequences.
We are at a similar inflection point today. Except the window is shorter. The technology is moving faster. And the concentration of ownership is, if anything, more extreme than it was in 1870.
A handful of companies — measured in dozens, not thousands — own the infrastructure on which artificial intelligence runs.
The data centers, the chips, the foundational models, the platforms through which billions of people will soon interact with machine intelligence. The decisions being made in those companies right now, about ownership and governance and the distribution of AI-generated gains, will shape economic life for generations.
Most of those decisions are being made without you.
The Backwards AI Economy
Let us be precise about what the backwards AI economy looks like — because it is already taking shape.
In today’s backwards model, AI-generated productivity flows in one direction: upward.
A company deploys AI to automate the work of a thousand employees. Costs fall. Profits rise. Those profits are returned to shareholders through dividends and buybacks. The thousand workers — whose labor, whose knowledge, whose human interactions trained the very models that replaced them — receive nothing. The communities that housed them, educated their children, and built the infrastructure that made the company possible receive nothing.
The shareholders receive everything.
This is not a hypothetical. It is already happening. It is the default outcome of the free-enterprise system we’ve built. If we do nothing — if we allow the backwards rules of the twentieth century economy to govern the most powerful technology in human history, a dim future awaits us.
Carried to its logical conclusion, the backwards AI economy produces a world in which a vanishingly small number of people own machines that do essentially all the productive work, and the rest of humanity must negotiate for whatever share those owners choose to offer.
That is not the future our Founders envisioned. But it will be the future we’ll inherit if we fail to act.
Our Collective Knowledge Inheritance — and Why It Changes Everything
Here is what the current owners of AI systems prefer you not examine too carefully.
The large language models powering modern AI were not built from nothing. They were trained on the accumulated written knowledge of humanity — every book ever digitized, every article ever published, every scientific paper ever shared, every conversation ever recorded online. The collective intellectual output of billions of human beings across centuries.
None of those people were compensated. None of them consented. The most valuable training dataset in human history was assembled from the “commons,” a term used to describe things that belong to the greater public, not any one person our group.
This knowledge represents the shared intellectual inheritance of our civilization — and used to build systems now worth trillions of dollars, the gains from which flow almost entirely to a few thousand shareholders.
The workers whose expertise AI encodes contributed their knowledge to this commons. The taxpayers whose investments built the internet, funded the research universities, and trained the engineers provided the foundation. The customers whose behavior AI systems learn from daily are providing continuous, involuntary, uncompensated training data. The power grid that powers the data centers was built over generations.
In a backwards economy, this is accepted as simply how things work.
In a forward economy, we must ask a different question: if AI was built using our shard inheritance, should we not all share in what it produces?
The answer, honestly arrived at, is yes.
One mechanism for making it real is the Forward Fund.
The Forward Fund as Steward of the AI Commons
The Forward Fund model, described earlier in this book, was conceived as a better way to organize businesses and distribute prosperity. It turns out to be something more: an institutional architecture with the capability to govern AI in the public interest.
Here is how it works applied to artificial intelligence.
AI systems built substantially on public knowledge and public infrastructure are held not by private shareholders but by Forward Funds — mission-locked institutions constitutionally prohibited from extracting value for private gain. The funds own the technology. But ownership, in this model, is public stewardship rather than private extraction.
The gains AI generates under this model do not flow to shareholders. They flow forward — into better models, broader access, lower prices, new applications, wages for workers whose productivity AI augments, and noble causes that workers themselves choose to fund.
The return to the public rests in the compounding capability that benefits everyone who uses it.
This is not charity. It is honest accounting — recognizing that AI was built on a foundation that belongs to all of us, and structuring the returns accordingly.
Competition, Productivity, and the Price of Progress
The obvious question — the one a skeptic will ask immediately — is this: without the profit motive, won't the funds stagnate? Won't collective ownership produce the inefficiency and inertia that has plagued every previous experiment in non-extractive economics?
The answer is no — and the reason why is the most elegant feature of the forward model.
The funds compete.
Not to maximize returns to shareholders — there are none. But to build better AI, serve more users, lower costs further, solve harder problems. Each fund is trying to out-innovate the others, because that is how it grows, attracts talent, earns trust, and fulfills its mission.
The competition between funds is what drives productivity into lower prices rather than into private pockets. When a forward AI fund develops a breakthrough that reduces the cost of medical diagnosis by 40%, it does not extract that gain as profit. It passes it through to users — because the fund's mission requires it, and because the competing fund down the road is doing the same thing and will capture the market if it doesn't.
This is the market mechanism working as it was always supposed to work — driving innovation and efficiency into broad social benefit rather than narrow private gain. The difference is not the absence of competition. It is the outcome that competition produces under the right architecture.
In the backwards model, competition drives companies to capture more value from users.
In the forward model, competition drives funds to deliver more value to users.
Same human ingenuity. Same drive to win. Completely different outcome — because the rules are different.
Splitting — The Architecture of Freedom
There is one more feature of the forward model that deserves careful attention, because it addresses the deepest concern about any new system of shared ownership:
What prevents the funds themselves from becoming the new monopolists?
The answer is structural, not regulatory. It is built into the forward governance architecture from the beginning.
When a Forward Fund reaches a defined scale — when it grows large enough that its decisions begin to shape markets rather than respond to them — it splits. One fund becomes two. Two become four. The capital, the talent, the mission, and the governance structure divide and replicate, like cells in a healthy organism.
This is not imposed from outside by regulators who may be captured, or by legislators who may be lobbied, or by courts that move slowly while technology moves fast. It is written into the fund's founding documents — a constitutional provision that activates automatically, requiring no enforcement because it requires no external authority to trigger.
The elegance of this mechanism is that it makes concentration of power that AI otherwise engenders essentially impossible by design. No single fund can grow large enough to capture the political system, distort the regulatory environment, or crowd out competition — because the moment it approaches that scale, it divides. The competitive landscape is self-renewing. The checks and balances are internal.
The Founders would recognize this framework immediately. Separation of powers. Checks and balances. Federalism. The entire American constitutional architecture rests on the same insight: that the most dangerous concentrations of power are not prevented by hoping those who hold power will restrain themselves, but by designing systems in which the ambition of others provides the necessary restraint. It becomes structural and automatic.
We built that architecture for government in 1787. We need to build it for the AI economy now.
Why the Timing is Right
There is a reason this chapter exists in a book about the forward economy rather than in a policy journal or a technology manifesto.
The argument for governing AI through Forward Funds is only as strong as the evidence that Forward Funds work.
Right now, that evidence does not yet exist at scale. The model is theoretically sound. The case studies point in the right direction. The logic is compelling. But a skeptic — a regulator, an investor, a legislator, a journalist — can reasonably say: show me.
That is why launching the first Forward Fund is not merely a business decision or a philanthropic gesture. It is a strategic act with consequences that extend far beyond the enterprises it initially contains.
Every year a functioning Forward Fund operates — sharing profits, reinvesting forward, splitting as it scales, demonstrating that virtue outcompetes extraction in a fair market — is a year of evidence accumulating. Evidence that the model works. Evidence that it is governable. Evidence that it produces the outcomes it promises.
And when the AI governance debate reaches its critical inflection — when the frameworks are being written and the institutional models are being chosen — the people arguing for the forward approach will not be speaking theoretically. They will be pointing to something real.
That proof of concept may be the most important thing this generation of forward-minded Americans can build. Not because it will be large at first. But because the right idea, demonstrated at any scale, at the right moment, can change the direction of history.
The Founders did not wait until they had a perfect union to declare one. They built the architecture as carefully as they could, launched it into the world, and trusted that the right design would prove itself over time.
That is what we are called to do now.
The Patriot's Argument
Let us be direct about what is at stake — not in alarmist terms, but in honest ones.
The health of a democracy depends on a rough balance of economic power among its citizens. Not perfect equality — no serious person argues for that. But a distribution of economic agency broad enough that ordinary people have a meaningful stake in the system and a meaningful voice within it.
When economic power concentrates beyond a certain threshold, democratic institutions bend toward it. Not always through corruption — often simply through the natural operation of influence, access, and the tendency of those who set the rules to set them in their own favor.
This is not a partisan observation. It is a historical one, visible across centuries and systems.
AI, governed by backwards rules, will concentrate economic power faster and more completely than any previous technology. The productivity gains will be real. The wealth created will be genuine. But under the wrong architecture, that wealth will flow to an extraordinarily small number of people and institutions — narrowing the economic base on which democratic participation rests.
America has navigated this challenge before. The Progressive Era. The New Deal. The postwar social compact that built the middle class. Each was an imperfect, contested, sometimes painful correction to a concentration of economic power that had grown beyond what a healthy democracy could absorb.
We can do this the hard way — wait for the concentration to become undeniable, then spend decades fighting to correct it after the fact.
Or we can do it the American way — design the architecture right from the beginning, before the rules harden, while the window is still open.
The Founders chose design over correction. They looked at the tyrannies of history and said: we can build something that makes that less likely — not by hoping for better rulers, but by creating a better system.
That is the patriot's argument for the forward AI economy. Not that the current path leads certainly to catastrophe. But that we have a choice, right now, that we will not have indefinitely — and that the right choice is the one our best traditions have always pointed toward.
Build the system that works for everyone.
Do it now, while we still can.
Do it because that is what Americans, at their best, have always done.