Refuting the “2028 Economic Collapse Theory”: AI May Cost You Your Job, But It Also Makes Everything Nearly Free
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Refuting the “2028 Economic Collapse Theory”: AI May Cost You Your Job, But It Also Makes Everything Nearly Free
This is not merely a crisis but a radical evolution toward a “post-human economy.”
Navigating Web3 tides with focused insightsAuthor: David Mattin
Translated and edited by TechFlow
TechFlow Intro: While the entire industry panics over Citrini Research’s vision of a “global economic collapse triggered by AI in 2028,” technology thinker David Mattin offers a radically different interpretation. He argues we are undergoing a “Global Intelligence Transformation,” rendering obsolete traditional economic metrics—such as GDP and unemployment rates. This article explores how, when intelligence becomes as cheap and abundant as air, income-side erosion is outpaced by an even faster collapse on the cost side—ushering in a new era driven by “intelligence output per unit energy.” This is not merely a crisis; it is a radical evolution toward a “post-human economy.”
Full text below:
Everyone is talking about Citrini Research’s paper, The 2028 Global Intelligence Crisis. It’s a brilliant thought experiment: a speculative news report from June 2028 imagining a cascading economic collapse triggered by artificial intelligence (AI).
What follows is a response to that piece. You can think of it as a creation in the same spirit as Citrini’s original: a speculative “reverse scenario.” It is an exploration of a new way of seeing—not a claim to possess all the answers (no one does). This article draws on years of research and analysis published by Raoul Pal and me at Global Macro Investor, and through our joint technology-focused research service, The Exponentialist.
Citrini Research’s paper has attracted enormous attention—and for good reason. It is a masterfully constructed thought experiment: a speculative briefing from June 2028 that rehearses an AI-triggered cascade of economic melt-up. The S&P 500 drops 38%. Unemployment hits 10.2%. Prime mortgage markets fracture. The private credit complex collapses under a series of correlated bets on white-collar productivity gains.
The scenario is logically coherent, its financial mechanics painstakingly detailed, and its core thesis—that extreme intelligence abundance destroys the very consumption economy it was meant to strengthen—is deeply provocative. Some parts may well prove prescient. Real turbulence lies ahead—even extreme hardship. The transition to an age of intelligence abundance will be anything but smooth.
For over five years, I have immersed myself in this line of thinking. I’ve been building frameworks to understand what happens when intelligence becomes abundant, when the AI–energy flywheel begins to spin, and when we shift from a human-centered economy to something utterly new. In my related writings, I describe this as a fundamental shift toward a new kind of economic system: a form of “Post-human Economics.” From that vantage point—and drawing on years of analysis—I now offer a considered response to Citrini’s argument, arriving at a markedly different conclusion.
Citrini’s argument is that abundant intelligence destroys the income side of the economy—wages, jobs, consumer spending—thereby triggering financial crisis. My argument is that abundant intelligence is simultaneously destroying the cost side of the economy—and doing so possibly faster. When prices for goods and services collapse alongside wages, you’re not facing crisis. You’re in the midst of a transition to an entirely new system—one where all the old norms, rules, and metrics lose coherence.
So what is the central error in Citrini’s article? They’re measuring a “post-human economy” with instruments designed for a “human economy.” Then they mistake the instrument’s erratic readings for systemic collapse.
No one has a crystal ball. No one holds all the answers. We’re all assembling a seven-dimensional puzzle no one fully understands. Yet I believe Citrini’s article—though sophisticated—may commit a profound and illuminating error. And my own work points directly toward it.
My time horizon is also longer than Citrini’s. Their scenario unfolds over two years. I’m observing transitions across ten- to twenty-year spans. I acknowledge serious turbulence lies ahead: a “Fourth Turning”–style moment of chaos, social unrest, and institutional breakdown. A version of what they describe may indeed arrive. But my argument is that AI—and the broader forces of the Exponential Age—will ultimately carry us into a genuinely new economy. One that functions well. One that, in many ways, is better than anything we’ve known before.
Wrong Metrics
This is the core claim I want to make—if I’m right, it reframes everything.
Every data point Citrini uses to build their argument—the 10.2% unemployment rate, the 38% S&P 500 decline, the surge in San Francisco mortgage delinquencies, the stagnation in velocity of money—is priced in the old system. Each metric originates in the economy we’ve always inhabited: one built around human labor input, material scarcity, and GDP as the scoreboard.
The authors look at these readings and see disaster—an understandable reaction. But what if these metrics aren’t recording the death of the economy? What if they’re recording the death of an “economic measurement framework” that can no longer describe what’s actually happening?
Flip the perspective. Citrini’s article centers on a powerful concept: “Ghost GDP”—output that appears in national accounts but never circulates in the real economy. They treat it as evidence of dysfunction. I reverse this entirely. Ghost GDP isn’t a bug—it’s a signal. It tells us that GDP itself, as a meaningful measure of present reality, is breaking down. The instrument is failing—and Citrini mistakes the failed instrument’s readings for the patient’s true condition.
In my work on post-human economics, I’ve argued that as we transition to an economy built on automated inputs and extreme abundance, GDP becomes incoherent. It cannot capture an economy where the costs of many goods and services are trending toward zero—unevenly, unevenly across domains, but undeniably falling. It cannot capture the massive uplift in human welfare when intelligence becomes extremely abundant and nearly free. And it cannot capture the rise of “autonomous economic activity”—transactions among AIs themselves—having no substantive link to human labor markets.
In the post-human economy, GDP is not a coherent measure of anything. So what should we watch instead?
Intelligence Output Per Unit Energy
This is my answer—and the idea sits at the heart of my thinking about the future post-human economy.
In the coming economy, the most coherent measure of prosperity is intelligence output per unit energy. How efficiently is our civilization converting energy into useful intelligence?
This is the metric that resolves the central paradox of the Citrini scenario. Because precisely as their scenario shows GDP shrinking, the S&P plummeting, and unemployment surging, intelligence output per unit energy is soaring vertically.
Think about what drives the crisis Citrini forecasts. AI models are growing stronger, compute costs are falling, and inference costs are crashing through the floor. AI-managed energy systems are becoming vastly more efficient. Every force—precisely those dismantling old economic indicators—is simultaneously rocketing “intelligence output per unit energy” skyward.
That’s the key insight: there are two lines on the chart. One line—GDP, employment, consumer spending—is descending. The other line—intelligence output per unit energy—is rising exponentially. Citrini’s article stares only at the descending line and concludes we’re in crisis. My claim is that the ascending line is the true signal—and the descending line is just noise from a dying system.
In a world where intelligence becomes profoundly abundant, everything sits downstream of better, more abundant intelligence. Scientific breakthroughs, novel materials, advanced medicine, cheaper energy, better infrastructure, more efficient manufacturing—all spring from the same source: our relentless, unrelenting improvement in converting energy into intelligence.
Citrini’s article looks at a GPU cluster in North Dakota and says: that machine just destroyed 10,000 white-collar jobs in Manhattan. I look at the same GPU cluster and say: that machine just collapsed the cost of drug discovery, materials science, legal services, education, energy management, and software development. Both observations are factual—but that article focuses exclusively on the income side of the ledger, barely glancing at the expenditure side.
And that is the deeper error.
Radical Prosperity
Yes, output is decoupling from labor markets. Citrini is right about that. But the same force that destroys wages also destroys costs. When AI pushes legal services toward near-zero pricing, you no longer need a $180,000 salary to hire a lawyer; when AI collapses diagnostic costs, you don’t need expensive health insurance to get diagnosed. When coding agents make software nearly free, Citrini’s anxiety over $500,000 annual SaaS renewals isn’t just a vendor problem—it’s a massive buyer saving.
Through the lens of GDP, this looks like a collapse of the consumption economy; from another angle, it’s the birth of deflationary prosperity—wealth generated by abundance. Even as nominal incomes fall, real purchasing power explodes. Ordinary people’s capacity to obtain goods and services surges in ways traditional metrics cannot capture.
If someone earns $50,000 in a world where AI has pushed healthcare, education, legal counsel, financial planning, software, entertainment, and creative services toward near-zero cost, are they richer or poorer than someone earning $180,000 in 2024?
Citrini’s paper never considers this. It tracks falling wages but ignores the simultaneous collapse in “costs required to sustain life.”
I can hear some readers screaming at me. I’m not naive. Some critical goods and services won’t fall in price quickly—or ever—like housing, physical food, and (at least for a while) energy. This process will be wildly unbalanced. Some domains will see cost collapse within years; others may take a decade or more. This transition will be painful for many—a crucial social reality we must confront, whose depth exceeds the scope of this essay, though I’ve written about it elsewhere. I’ve written about the “sharp turn” ahead and warned that a “Fourth Turning” moment is highly likely. There will be social and political upheaval—I do not dispute that.
The Foundation Layer Flywheel: The Real Brake
But Citrini’s scenario frames this transition as a one-way spiral into destruction. They claim there’s no natural brake—no bottom to the displacement loop.
I disagree. The brake is abundance itself.
That brings us to the engine I call the Foundation Layer Flywheel.
As early as 2023, I wrote about the deep symbiosis between AI and clean energy. AI demands massive energy—but AI is also the only technology capable of managing the incredibly complex, distributed energy systems we’re building. More AI unlocks more energy; more energy powers more AI. Round and round.
This flywheel is the bedrock of the entire Exponential Age. It supports everything happening above it. That’s why Citrini’s displacement spiral has a natural brake—one their model fails to account for.
As intelligence output per unit energy rises, the flywheel spins faster. Cheaper, more abundant AI makes energy systems smarter; smarter energy systems deliver cheaper energy; cheaper energy makes AI cheaper. Cheaper AI then permeates everything downstream: cheaper materials science, cheaper manufacturing, cheaper healthcare, cheaper infrastructure.
Citrini’s article imagines a negative feedback loop: AI destroys jobs → unemployed workers spend less → companies buy more AI → repeat, with no natural brake.
But running parallel—and at least as powerful—is a positive feedback loop: AI grows smarter → energy gets cheaper → intelligence output per unit energy rises → costs collapse across the entire downstream intelligence stack → living standards improve materially, even as nominal GDP shrinks.
Which loop dominates? That’s the question. In my view, the positive loop has physics on its side. It’s driven by exponential improvement in converting energy to intelligence—a curve that has steepened for years with no sign of slowing. By contrast, the negative loop is driven by institutional and political inertia: slow-moving mortgage markets, fiscal policy, labor market adjustments. These are real—and cause real pain—but they are not immutable natural laws. They are human constructs, and humans can change them.
AI and Robotics Are Demographics
There’s one more thing Citrini’s article completely overlooks—and it’s one of the most important macro forces of our age.
Demographics.
Developed nations are shrinking their labor forces. Working-age populations in the U.S., Europe, Japan, South Korea, and China are plunging sharply. This is the demographic doom loop I’ve often written about. Fewer babies, longer lives, towering population pyramids—none of this has ever existed in human history.
As Raoul has long emphasized, the golden rule is: GDP growth = population growth + productivity growth + debt growth. Population growth is gone. It’s been gone for some time. That means the only way to keep the GDP game going is to increase debt. We borrow tomorrow’s money to fund today’s party.
Now consider what happens when AI and humanoid robots enter this environment. Citrini’s article frames the arrival of machine intelligence as an invasion of a healthy labor market. AI bursts through the door, discarding millions of workers.
That’s the economy emerging on the far side of the singularity. Not a silent zone of mass unemployment—but a world where the old economy has been composted to nourish something entirely new, strange, and in many ways richer.
But that’s not accurate. AI is entering a world that desperately needs it. We’re short-handed. The working-age population in the Global North is falling fast—and without AI and robotics, GDP growth would face structural decline regardless.
Kevin Kelly calls what’s coming “the handoff.” As human populations peak and decline, billions of AI agents and millions of humanoid beings flood in to fill the void. We’re handing the economy over to non-human actors.
This doesn’t eliminate the pain of individual transition. People losing real jobs face real hardship—we must confront that head-on. But macroscopically, AI and robotics aren’t replacing workers—they’re filling a demographic vacuum that would otherwise swallow the entire economy.
Citrini’s scenario envisions a world where AI destroys the job market and no one can find work. But what if reality by 2028 looks more like this: AI and humanoid beings fill millions of roles vacated by labor shortages, while humans displaced from knowledge work—painfully, but with support—migrate into the emerging economy I’ll describe next?
The Human Residue
Because this is something Citrini’s article never considers. As the old economy contracts, a new economy is self-organizing from the ground up.
I’ve written about the rise of independent industrialists. Sam Altman talks about billion-dollar companies run by one person. In certain fields, AI tools and agents allow a single high-productivity individual to produce output once requiring hundreds of employees. We’ll see millions of such new economic participants—independent operators and micro-teams managing large swarms of AI agents—creating immense value in ways the old economic framework could never foresee.
Anthropic’s research into how people use Claude reveals the contours of this future. Software development. Consulting. Financial services. Marketing. Content creation. In every domain, high-capability individuals augmented by AI are becoming one-person enterprises. This is new economic activity—and most of it will occur outside the structures Citrini’s work monitors.
But a deeper transformation is underway. As machine intelligence takes over all cognitive labor—coding, legal documentation, financial analysis, data processing—economic value migrates up Maslow’s hierarchy, toward levels only humans can provide.
I call this “the Human Residue”: value creation that requires being human. It’s the attention, empathy, and recognition of another person who truly sees you. It’s art and narrative from authentic, lived experience. It’s the counselor helping you navigate a stressful move, the guide supporting you through a life crisis, the community builder creating spaces where you feel you belong.
When AI handles all the paperwork, what remains scarce? Feeling. Connection. Meaning. Around these irreducibly human outputs, a vast new economy will form. It will generate enormous value—but it won’t register in GDP, nor will it be captured by the metrics Citrini’s article tracks.
That’s the economy emerging on the far side of the singularity—not a dead zone of mass unemployment, but a world where the old economy is composted to nourish something new, strange, and in many ways richer.
System Transition
Let’s tie it all together.
Citrini’s article poses a central question: What happens when a previously scarce input—intelligence—becomes abundant?
It’s the right question. Across modern economic history, human intelligence has been the scarce, premium-priced input. They’re correct that this premium is vanishing—and it is. On an increasing number of tasks, machine intelligence has become a competent—and rapidly evolving—substitute for human intelligence. On that point, we agree.
But Citrini concludes that the vanishing of the human intelligence premium equals “crisis.” I argue it’s “transition.” They’re staring at the dissolution of the caterpillar and screaming that the organism is dying. In a sense, they’re right—the caterpillar *is* dying. But something else is forming inside the chrysalis.
What’s forming is a post-human economy. In this economy, intelligence is no longer scarce—it’s abundant as air. In this economy, knowledge work—and eventually much physical production—will trend toward zero cost—not overnight, not evenly across sectors, but relentlessly. In this economy, the fundamental measure of prosperity shifts from how much nominal economic output we produce to how efficiently we convert energy into intelligence. In this economy, the value humans exchange with one another migrates from cognitive labor to deeper layers: empathy, meaning, connection, creativity, and the sheer experience of living alongside other conscious beings.
We are not heading toward a “global intelligence crisis.” We are entering a “global intelligence transformation.” We are stepping into a wholly new economic system—one all of us are struggling to understand. Yes, the transition will be turbulent—even violently disruptive. There will be chaos, pain, and political shockwaves. A “Fourth Turning” is likely real. Some scenarios Citrini describes—unemployment, SaaS industry collapse, frictionless markets—are likely arriving, and faster than most expect.
But viewed over the longer time horizon I observe—ten to twenty years, not just two—their conclusion begins to crumble. A depression rivaling the Global Financial Crisis (GFC), with a 57% drop and no natural brake? That conclusion rests entirely on the assumption that the old metrics still reflect system truth.
I don’t believe they do. There will be real pain—but that pain is characteristic of transition, not evidence that the destination is inevitably catastrophic.
There are two lines on the chart:
- GDP is falling.
- Intelligence output per unit energy is rising.
One line is the real signal. The other is just noise from a dying measurement system.
If we want to understand what’s happening all around us, we must ensure we’re watching both lines.
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