Path to Abundance

The Most Optimistic Future in Human History Is Within Our Reach

The world is standing at the edge of something enormous, and the real story is far bigger than the headlines have let on. Artificial intelligence is moving faster than almost anyone predicted. The lesson of the past few years turns out to be surprisingly simple. Scaling works. Give these systems more computing power and better methods and they get smarter, and then they keep getting smarter. The next wave of hardware, the chip platform Vera Rubin, paired with the fresh algorithmic breakthroughs arriving almost every week, will be powerful enough to push us across a remarkable line.

By 2027, I expect us to reach artificial general intelligence. That is the moment a machine can match every human expert across every one of the thousands of specialized fields we have built over our entire history. A doctor, a lawyer, a chemist, a coder, a composer, all at once, on demand.

This sets off a massive transition. The next 12 to 18 months are the window where we get to shape that transition, and with it the future of humanity. It is the window where artificial general intelligence changes everything and swings open the door to genuine abundance. Many people still have no idea this is happening, and a growing number are simply afraid.

I wrote this deep dive to show you the other side of that fear. I want you to see the real, concrete chance we have to build a world of abundance. A world where poverty is erased, where every disease is cured, where energy is plentiful and production runs itself, where the painful problems that have defined human life finally become solvable, and where humans are free, at last, to be fully human.

A world of abundance is within our reach. Real challenges and obstacles stand between us and it, and we will face them honestly in this deep dive. Through all of it, please hold on to this: we are living through the most hopeful period humanity has ever known, and there has never been a better time to be optimistic about what lies ahead.

I do not own a crystal ball. Many things could knock us onto a completely different track. What I do is follow this technology closely, study the trends, and project where they point. Treat what follows as an educated guess from someone watching the data every day. Also treat it as a call to action, and as a picture of a future worth getting excited about and worth standing up to demand.

The Risks Are Real. Let’s Face Them First.

AI is a force with no polarity, the way fire and electricity have no polarity. Aim it well and it lights up the world. Aim it badly and it burns. I name the dangers plainly here because the bright future I am about to describe depends entirely on us seeing them clearly.

If we let things run on their current track, AI will deepen the inequality and division already straining our societies, and that path leads somewhere dangerous, toward civil unrest, political extremism, and real human suffering. The earliest deployments of this technology have mostly served a powerful few. Companies have used it to cut costs and lift productivity with little thought for the workers left behind. Militaries race to field autonomous weapons. Surveillance systems grow sharper and more all-seeing. A small group of people has been handing itself the most powerful tool on Earth and using it to gather more power.

AI and advanced robotics are moving from tools that assist human workers to systems that replace them entirely. Unlike every previous industrial disruption, this one threatens cognitive work alongside physical work simultaneously. The social contract that held through earlier technological shifts, the implicit promise that a displaced worker could always find a new role somewhere, is under genuine strain for the first time in modern history.

Besides the economic issues, there are also three deeper risks underlying all of this. The first is alignment, the unsolved challenge of keeping an AI’s goals tied to ours. The danger here is subtle. Picture a brilliant system pursuing an objective that is perfectly logical to the machine and quietly catastrophic for us. The second is autonomous weapons, machines that can search for, choose, and strike targets with no human hand on the trigger, draining conscience out of warfare and replacing it with calculation. The third is surveillance and control. When governments and corporations use AI to track, predict, and nudge human behavior at scale, democracies risk hardening into glass houses and authoritarian regimes risk becoming nearly impossible to dislodge.

The destination is genuine abundance, and getting there safely is the work. Keep both of those in view as we go.

The Forces That Cannot Be Stopped

Here’s a truth that can feel uncomfortable until you accept it, and then becomes clarifying: nothing and nobody will stop the advancement of AI and automation. This isn’t fatalism. It’s an understanding of the incentive structures that now govern the world.

We’re in the geopolitical equivalent of an arms race. The competition between the United States and China for AI supremacy has become the defining rivalry of the 21st century, a Cold War 2.0 where the prize is technological dominance. Neither side is going to blink. AI, robotics, and automation are now first-class political and capital priorities for both major powers, and that guarantee alone will sustain relentless development.

Add to that the raw scale of private investment. The AI infrastructure buildout is the largest private megaproject in human history. By the end of this decade, we’ll have spent trillions of dollars on data centers, chips, and AI systems. That investment has already eclipsed the Manhattan Project and the Apollo programme combined.

And then there’s the most powerful force of all: ordinary economic rationality. When it comes down to it, every business, household, and government reaches for the cheaper option, even when the cheaper option is rough around the edges. As AI and robotics scale, automated goods and services become dramatically cheaper, and they end up faster and better too. Multiply that single preference across the world, and you get what is called an attractor state, a destination the whole system slides toward on its own. The endpoint is a maximally automated economy, production and defense included, arriving first in unregulated private fields and eventually everywhere.

One more accelerant is worth understanding, because it is the engine under the hood. We are in the early stages of recursive self-improvement. Everything now hinges on a single loop: whichever AI model generates the best code can build the best AI researcher, which generates even better AI, which writes even better code, round and round, each turn faster than the last. Code is the critical path to maximum acceleration, and optimization then flows from the top of the stack, the software and algorithms, down through the hardware and energy and the very substrate of computing.

The wave is coming. There is no stopping it. Our job is to shape how it lands.

The Economy Is Already Shifting Under Our Feet

You might be thinking this all sounds theoretical. It isn’t. The post-labor economy is not a forecast for some distant future. It’s the landscape we’re navigating right now, and the evidence is becoming unmistakable.

Consider what’s happened to entry-level jobs. Randstad’s 2025 Gen Z Workplace Blueprint, which analyzed over 126 million global job postings, found that positions requiring zero to two years of experience have contracted by 29 percentage points since January 2024. Junior technology roles specifically are down 35%. Finance is down 24%. Meanwhile, the New York Fed’s labor market tracker found that recent college graduate unemployment sat at roughly 5.7% in early 2026, with the underemployment rate, graduates working in roles that don’t require a degree, stuck above 41%. These are structural signals.

Corporate America is becoming increasingly direct about the cause. Cloudflare eliminated over 1,100 positions explicitly described as made obsolete by AI, while simultaneously reporting record revenues. Intuit announced a 17% workforce reduction of roughly 3,000 employees to refocus on AI. GM cut hundreds of salaried technology workers while openly hiring for what it called “AI-native engineering” roles. Block’s Jack Dorsey executed a 40% workforce reduction citing AI-driven productivity gains. A year ago, these announcements came wrapped in euphemisms like “restructuring” and “efficiency initiatives.” Today, executives say it plainly.

Challenger, Gray & Christmas tracked AI as the primary driver of US layoff announcements for three consecutive months in spring 2026, with AI-attributed cuts reaching nearly 88,000 in just the first five months of the year. Stanford’s Digital Economy Lab published econometric research demonstrating a 16% relative decline in employment for early-career workers in the most AI-exposed occupations since generative AI went mainstream, controlling for interest rate effects and broader macroeconomic factors.

Here’s the subtler dynamic that matters even more. The Magnificent Seven tech companies are collectively spending between $700 and $800 billion on AI infrastructure in 2026, a 77% increase year-on-year. In any previous era, that level of capital deployment into an industry would produce millions of new jobs. This one is producing tens of thousands. The investment flows to servers and silicon, to shareholders and compute rather than workers. In a previous age, economic growth and job creation moved together. We’re watching them decouple in real time.

This is how automation reshapes an economy. The layoffs that make headlines are visible and dramatic. The jobs that simply never materialize are invisible and arguably more significant. When GDP growth stops translating into employment, under a regime of advancing automation, that divergence is economically equivalent to jobs being eliminated. The apprenticeship layer of the economy is being quietly automated away. The career ladders that young people expected to climb are missing their first several rungs.

Underneath all of this is a deeper structural pattern. Automation doesn’t destroy the economic value of the tasks it performs. The tasks still get done and still produce output. What it does is relocate the income from those tasks out of wages and into capital, one task at a time. Income that used to flow to workers now flows to the owners of capital, distributed according to how much capital you already own. This is the mechanism by which the economy leaves workers behind while aggregate output keeps rising.

Letting Go of the Old World

There’s a deeper question underneath all the economic data, and it’s worth thinking about it. Why are we so attached to the idea that work must be the organizing principle of human life?

Think about what wage labor has actually asked of most people throughout history. Trade your most productive hours. Sacrifice time with your children during their most formative years. Grind your health down into something called a pension that you may or may not live long enough to enjoy. The system promised that if you paid that price, you’d earn security. That bargain was never generous. It was simply necessary, because there was no alternative.

AI, implemented thoughtfully, dissolves that necessity. The machine works. You live. The machine produces. You create from overflow rather than from desperation. That inversion sounds almost too simple to take seriously, which is exactly why so many people instinctively resist it.

People often argue that labor builds character, provides purpose, and structures human existence in healthy ways. There’s something real in that. Human minds and bodies genuinely do flourish when they’re striving toward worthy goals. But conflating “humans need purpose” with “humans need wage labor” is an error. Purpose and survival-driven employment are two very different things. One is a deep human need. The other is a particular economic arrangement that has existed for a few centuries.

The historical record is instructive. Charles Darwin never worked in the conventional sense. He was a member of the landed gentry, chronically ill, financially secure enough to spend decades thinking carefully about what he observed. His scientific productivity was enabled by security. Aristocrats and nobles throughout history, for all their many flaws and moral failures, did not fill their freedom with vacancy. They became astronomers, composers, philosophers, inventors, and art patrons. They had time and agency. They filled that space with contributions we still remember.

The suggestion that ordinary people, given genuine security, would choose to do nothing is an idea invented by those who benefit from keeping you afraid and compliant. Look at what people do with the scraps of time and energy left after work’s demands are met. They write. They coach youth sports. They make music. They care for sick relatives. They build community organizations and learn new crafts. That is what humanity does when the mandate to survive is lifted even slightly.

Capitalism, for its part, has no opinion about whether humans work. It cares whether goods and services get produced and bought. It is the most ruthlessly pragmatic system ever devised, perfectly indifferent to whether the inputs on the supply side are human hands, steam engines, or neural networks. It seeks the cheapest, fastest, most efficient path from production to consumption, and that is the whole of it.

With AI and robotics we are arriving at the point where we can end economic dependence on employment altogether, so that people can chase what they actually want.

Instead of excitement over the end of tedious labor, a wave of anxiety has taken hold. This fear so many people feel is a blend of two things, dread of what they do not understand and a wounded pride at losing our perch as the smartest entity around. Sigmund Freud once described three great blows to human self-importance. Copernicus showed we are not the center of the cosmos. Darwin showed we are animals among animals. Freud himself argued we are not even masters of our own minds. AI may be the fourth blow.

People have been handed a frightening picture of this future and almost no hopeful one, and that gap is a serious problem. Closing it is why I write. For decades, people have been told their lives are getting worse, a story that keeps everyone in survival mode, working hard, easy to manage. The reality is that the average person today lives better than 18th-century kings, and the trend keeps improving. With AI and robots, life is about to get dramatically better, by orders of magnitude, over the next 10 years.

The Engine of Abundance: When Intelligence Becomes Unlimited

To understand what’s actually coming, you need to understand one pattern that runs through the whole of human history. Every great civilizational leap was triggered by solving a single, critical scarcity.

The Industrial Revolution was fundamentally about muscle. Before the steam engine, all meaningful physical work was bounded by the strength of humans and animals. The engine cracked that ceiling open. The Digital Revolution was fundamentally about distance. Before the internet, information moved at the speed of trucks and planes. The bit collapsed geography. Both revolutions transformed everything by making one previously scarce resource effectively unlimited.

The revolution we’re entering today is about intelligence. Throughout all of human history, the hardest single constraint on progress has been the number of trained, expert minds available to work on the world’s most important problems. Designing a novel drug, diagnosing a complex patient, proving a mathematical theorem, engineering a fusion reactor: these tasks have always been rationed by the tiny, expensive pool of people capable of performing them.

What happens when that pool becomes effectively infinite? We will solve everything.

Two milestones mark the path. Artificial general intelligence, or AGI, is the point where a system is as capable as a human expert across all economically valuable tasks. If you can hire a person to do it, an AGI can do it too, and I expect this to be common and accessible by 2027. Artificial superintelligence, or ASI, is the moment AI exceeds human ability by orders of magnitude, having synthesized more information than every human who has ever lived, combined.

We get to AGI and ASI through several reinforcing routes: scaling compute, models, and data, steady algorithmic improvements, new architectures, recursive self-improvement where AI speeds up AI research, multi-agent coordination, and ever-greater compute efficiency that widens access.

Three trends are converging to make all of this possible at breathtaking speed. The raw quality of AI models is advancing past human performance benchmarks with each passing month. The cost of running AI, the unit cost of cognition, is dropping toward its physical limit: essentially the price of the electricity. And the friction of deploying AI into the real world is approaching zero.

When superhuman thought becomes as cheap as electricity, we can direct computing power toward any problem. Every domain becomes “compute-bound”: you get reliable results simply by running more computation. That’s what it means for a domain to be “solved.” What was once a craft accessible only to a world-class expert becomes a system accessible to anyone.

One more critical point: AGI won’t just solve individual problems one at a time. We will build industrial systems that solve entire fields at once, the difference between discovering a single new drug and building a platform that can cure any pathogen on demand.

Abundant high intelligence will solve every major problem and enable genuinely unlimited economic growth. That’s the foundation everything else is built on.

What Abundance Actually Looks Like

Let me take you somewhere. Picture the world that emerges on the other side of this transition.

Your personal health agent monitors your biological state continuously, catching cell errors before they become tumours, adjusting your nutrition based on your real-time proteomic data, and flagging anything that needs professional attention. Personalized gene therapies designed specifically for your DNA can be synthesized within hours. Highly precise robotic surgical systems make complex procedures accessible to everyone, anywhere, at no cost. The “Virtual Cell,” a complete high-fidelity simulation of human biology, has turned every disease into a software problem that can be fixed. And longevity science has crossed what researchers call Longevity Escape Velocity: for every year you survive, science adds more than a year back to your clock. Aging has become a manageable condition rather than a destiny.

Look at energy. Autonomous systems have carpeted sun-drenched deserts with next-generation photovoltaics. AI-designed solid-state batteries store midday abundance for the night, turning the sun into a reliable 24-hour power source. Intelligent software manages fusion reactors and global solar grids, delivering essentially limitless clean energy at a fraction of today’s cost.

Look at food. AI-managed vertical farms and synthetic biology grow abundant, nutrient-dense food using 95% less land and water, freeing vast territories for ecological restoration. Autonomous supply chains handle everything from robotic mining to drone delivery. Advanced recycling and manufacturing create goods on demand, making everyday physical items effectively free.

Every child has a personal AI mentor that adapts to their curiosity and learning pace, delivering bespoke education that was previously available only to the very wealthy. Climate engineering systems actively reverse centuries of industrial pollution. Heavy industry has moved to orbit, uncoupling Earth’s economy from its fragile biosphere.

Abundance, in this world, covers the full spectrum of human need. Material abundance at near-zero cost. And critically, non-material abundance: access to extraordinary creative output, genuine human connection, and above all, optionality. The freedom to choose what matters to you. It is a world of agency to live without the constant background fear of bills and survival. Survival is no longer the price of existing.

The Roadmap: Three Phases to an Abundant World

The path from here to that world isn’t magic. It follows a predictable sequence of compounding breakthroughs.

The first phase, covering roughly 2026 through 2027, conquers the digital realm. Mathematics and formal logic are already being verified by AI more reliably than any human. Computer science is following closely. Physics is next, as AI-powered simulation tools mature to model everything from quantum particles to astrophysical structures. When we can simulate the laws of physics with perfect fidelity, we gain the ability to design materials and molecular compounds that human chemists could never have reached through trial and error.

The second phase, from roughly 2028 through 2031, applies that mastery to matter itself. Chemistry and materials science become systematically solvable: research facilities run continuously, with AI handling the entire design-make-test cycle without human intervention. Biology follows. Once we have a high-fidelity simulation of a living cell, and from there an organ, and from there an entire organism, biology becomes a software problem. Every disease, including aging, becomes fixable. Ray Kurzweil’s predictions about biological mastery, made decades ago, will arrive roughly on schedule.

The third phase, from about 2032 through 2035, attacks the great civilizational infrastructure challenges. Fusion energy deployed at scale, integrated with vast solar grids and AI-designed grid storage. Autonomous systems expanding human presence into orbit, the Moon, Mars, and the asteroid belt. The physical infrastructure of abundance, built by machines, operated by machines, and accessible to everyone on Earth.

This is the trajectory current trends are pointing toward. It’s a projection taken seriously, built from the data and the trendlines.

When Abundant Intelligence Rewrites the Rules of Economics

There’s an assumption baked so deeply into classical economics that most economists don’t even notice it: intelligence is scarce. All of economic theory, from how wages are set to how markets clear to how institutions are designed, was calibrated for a world where expertise accumulated slowly and cognition was a limited resource.

When intelligence becomes abundant, replicable, and continuously improving, the foundational bottleneck of the entire system dissolves. Expertise scales instantly rather than accumulating over decades. Innovation shifts from a slow, generational process to real-time iteration. The machinery of economics, built to manage scarcity, starts to misalign with the new reality.

The practical consequence: AI and robotics will massively increase real economic output while simultaneously collapsing the cost of producing it. Roughly 60% of the cost of any good or service is ultimately labor. When labor costs collapse, prices collapse with them. The result isn’t deflationary depression, where falling prices reflect falling output. This is something different: price deflation driven by exploding productivity, where your purchasing power doubles even as your nominal income stays the same. If prices drop by half, you can buy twice as much. That is a real income increase felt by everyone.

The end point of this process, when AI can meet virtually unlimited demand for virtually anything at near-zero cost, is a genuine post-scarcity economy. The things that are expensive today, from personalized medical care to world-class legal advice to exceptional education, will reach the accessibility of a utility. Things that are rare today will be generated in essentially unlimited quantities for almost nothing. In the process AI will saturate demand for almost everything. The concept of scarcity, the organizing principle of all previous economics, will apply only to a narrow set of genuinely finite resources and experiences.

How the Economic Transition Could Unfold

Let me walk you through the three stages of economic transition to a world of abundance as they’re currently expected to play out, if we manage to go down this path.

The first stage runs from approximately 2026 to 2029. This is the AI implementation period. We reach AGI around 2027, productivity surges, prices begin to decline, and real incomes rise across the board. Some workers are displaced and find new roles in the short term. This phase is disruptive but manageable, because governments, with expanding tax revenues from a booming economy, become more generous with support programmes.

The second stage, from roughly 2030 to 2033, is when full unemployment arrives. AI and robotics exceed human capability across all domains and expand rapidly to fill every remaining job. When machines can do all jobs better and cheaper than humans, permanent unemployment happens relatively quickly. Everyone who becomes unemployed receives Universal Basic Provisioning (a mix of Universal Basic Income, Universal Basic Services, Universal Basic Equity, Universal Basic Compute). Because AI and robots will have significantly raised economic output, governments will have the capacity to afford Universal Basic Provisioning by pivoting from income and payroll taxes to a mix of taxes like automation taxes and sales taxes.

The third stage, from about 2033 to 2040, sees the economy continue expanding at speed. Output is no longer constrained by the limitations of human labor. This is when we will reach genuine post-scarcity. Demand for most goods and services reaches a maximum beyond which people simply don’t want or need more. From here the economy may ultimately evolve to one where all the basics of life are simply provided to everyone at no charge. This is not a wishful fantasy about government generosity. It’s the rational policy response to an economy producing vastly more than it needs to spend to maintain the wellbeing of its population.

The Architecture of a Post-Labor Economy

To give the economic side of the transition a bit more color, I want to introduce you to a framework which addresses the most important question for the next decade: do the gains from all of this flow to everyone or just to those who already own the most? That outcome, says post-labor theorist David Shapiro, is entirely a policy choice. And there is a clear architecture for getting it right.

The framework begins with understanding where household income comes from. Every dollar in your pocket originates from one of three sources: wages from selling your time, returns on capital from owning productive assets like stocks or real estate, or transfers from government programmes. The median American household today gets about 82% of its income from wages, 13% from government transfers, and just 5% from capital. When wages shrink as a share of the economy, as they’ve been doing for fifty years and as AI will dramatically accelerate, the other two categories must expand to fill the gap. Capital income and transfers must pick up the slack.

But here’s the problem with relying on transfers alone. A population that depends entirely on government transfers is a population whose livelihood can be held hostage by whichever politicians happen to be in power. Benefits get means-tested, conditioned, and cut. Transfers are essential and must remain a universal floor, but the destination is a capital-centric model where every household owns a share of the productive economy.

There’s also a darker problem Shapiro identifies that he calls “double bilateral dependence.” Throughout all of human history, the relationship between people and state has been a two-way dependency: governments needed citizens for labor, taxes, and military service, while citizens needed governments for safety and the facilitation of commerce. That mutual need created citizens’ bargaining power. When AI and robotics can conduct both labor and warfare, governments no longer need citizens for either. The leverage of ordinary people in the political system disappears unless we deliberately build new forms of it into the architecture of the new economy. Shapiro calls this “algorithmic rights”: legal and technical mechanisms that give ordinary people genuine control over the financial and data flows of an automated economy.

Shapiro’s framework for Universal High Income rests on multiple interlocking building blocks.

The first is the universal transfer floor: some form of Universal Basic Income (UBI) puts cash in people’s pockets when the labor market fails to. This infrastructure already exists in expanded forms, with over 100 US cities having run guaranteed income pilots since 2020 and 31 states running their own earned income tax supplements. It needs to scale dramatically.

The second is public capital through sovereign wealth funds. Norway’s Government Pension Fund now holds roughly $2.2 trillion. Singapore’s combined funds hold about $1.4 trillion for fewer than six million people, roughly $230,000 in public capital per citizen. Over 100 sovereign wealth funds exist worldwide, collectively managing over $13.7 trillion. Alaska’s Permanent Fund has paid per-capita dividends to every resident since 1982 and reduced poverty by 20 to 40%, with no negative employment effect. These funds invest public capital and distribute returns as dividends. Every level of government can operate such funds simultaneously, meaning every citizen eventually receives dividends from multiple streams just by existing as a member of society.

The third building block is Universal Basic Capital through baby bonds. The biggest barrier to capital ownership is that it requires money to make money. Baby bonds solve this directly: a government seed investment for every newborn, compounding for 18 years, gives every young adult a meaningful capital base generating returns for life. Connecticut launched the first state programme in 2023. Federal “Trump Accounts” created in 2025 provide a $1,000 seed for every child born between 2025 and 2028.

The fourth is private capital through employee ownership. There are currently more than 6,600 Employee Stock Ownership Plans in the US, covering over 15 million participants. ESOP workers typically hold roughly twice the retirement savings of comparable non-ESOP workers and 2.3 times the net worth. An estimated 2.3 million baby-boomer-owned businesses need succession plans in the coming decade. Every one is a candidate for employee ownership conversion. Cooperative models like Mondragón in Spain demonstrate this works at scale with 80,000 worker-owners. Decentralized Autonomous Organizations, or DAOs, are creating new forms of digital collective ownership that didn’t previously exist.

The fifth building block is a revenue pivot. Income and payroll taxes together account for 80 to 85% of federal revenue, and both are directly tied to wages. As wages shrink as a share of national income, this revenue base erodes. The solution is to tax other things: a value-added tax on consumption, an automation or capital services tax that replaces eroding payroll taxes, a land value tax, and data royalties that compensate citizens for the commercial use of collectively generated data. The critical principle is that new revenue sources must be generating receipts before the old ones collapse.

Stack all of these together and run the convergence modelling across multiple scenarios. The moderate result produces a median household income of roughly $140,000 in constant 2024 dollars, compared to about $83,730 today. That income flows from nearly a dozen distinct sources rather than the single paycheck that 82% of households currently depend on entirely. That diversification is itself a resilience feature. The system transforms from “tax and redistribute” to “own and distribute,” linking everyone’s income to the growth of the overall economy.

Besides David Shapiro’s concept and the widely discussed Universal High Income, several other ideas are pointing in the same direction. Universal Basic Services proposes that governments guarantee everyone access to essentials like healthcare, education, housing, and transport, free at the point of need. Universal Basic Compute suggests that every person should receive a baseline allocation of computing power, giving individuals direct access to AI and the infrastructure that increasingly drives economic value. Universal Basic Dividends is similar to Shapiro’s concept, distributing a share of the wealth generated by collectively owned resources back to the public as regular payments. Different names, different mechanisms, but the same underlying conviction: that the gains from our shared future should be shared broadly.

From Doing to Being

Let me address the concern I hear most often when I describe this future in more detail. If people don’t have to work, won’t they just drift into passivity?

I think that question gets the premise exactly backward. Consider what Universal High Income would actually mean for the psychology of everyday life. It would mean waking up without the background anxiety of rent and bills and status that shapes almost every decision most people make today. Imagine choosing what you do each day based on meaning, curiosity, love, beauty, mastery, and community rather than economic desperation.

Some people would drift initially. That’s honest. We will have to sit with ourselves and face what we have been running from. For a lot of people that becomes a genuine psychological and spiritual reckoning. But consider the alternative view of human nature, the one supported by actual evidence. Look at what people already do with whatever free time they have left. They write essays, make music, or coach youth sports. They build community organizations and learn new things. They garden, volunteer, create, and connect. The current system rations free time so severely that these pursuits are squeezed into evenings and weekends, what energy remains after the day’s mandatory labor is delivered.

Aristocrats and nobles throughout history didn’t fill their freedom with vacancy. They became collectors, scientists, composers, art patrons, philosophers, and explorers. We remember many of their names not because they held jobs but because they had agency. The suggestion that ordinary people, given equivalent security, would choose nothing is contradicted by almost all available evidence.

The psychologist Abraham Maslow built a hierarchy of human needs that runs from the most basic survival needs at the bottom up through belonging and esteem to what he called self-actualization at the peak: the drive to realize one’s full creative, intellectual, and relational potential. For most of human history and for most people alive today, the lower levels consume everything available. An economy of abundance, properly designed, lifts every person to the point where the upper floors become livable. Creativity. Deep learning. Genuine human connection. Community building. The full expression of what a human being can be.

We will shift, gradually and then rapidly, from a psychology of doing to a psychology of being. The status that today comes from professional titles and income will realign with what is actually valuable: being a good partner, a good parent, a good friend, and a genuine contributor to the communities that matter to you. That isn’t a utopia. It’s a civilizational upgrade that human beings are fully capable of embracing.

The Window Is Open. We Need to Step Through It.

Abundance for all is the possible outcome. It’s not the automatic one.

Look at the Industrial Revolution. That transformation generated extraordinary wealth. It also generated child labor, 60-hour work weeks, and urban poverty on a scale that took decades of labor organizing, progressive taxation, and social insurance to even partially address. The abundance was real. Its distribution across society required deliberate, often hard-fought political action. Left entirely to market forces, it concentrated.

The same dynamic is at work now. AI will produce abundance. The mechanisms by which that abundance reaches ordinary people require deliberate design and political will. Productivity gains flow to the owners of productive assets by default. They flow to workers and citizens only when we build the transfer structures, tax frameworks, and public investment vehicles to make that happen. “AGI will bring great abundance” is only half of the full truth. The complete picture: AGI will bring great abundance, and without deliberate design, most of it will not reach most people. This is simply how economics works.

The AI industry is raising the alarm and cannot change course, because its core business model runs on the very disruption it warns about, and its faith in full automation only makes it go faster. Policy is beginning to move, though it needs to accelerate dramatically. California Governor Gavin Newsom signed an executive order in May 2026 directing state agencies to build AI workforce-disruption dashboards and explore worker ownership models. The US Department of Labor launched an AI Apprenticeship Innovation Portal in April 2026. UK investment minister Lord Jason Stockwood publicly described UBI as a viable soft landing for AI-displaced industries. The Anthropic Economic Index, now published quarterly, has become the closest thing to real-time measurement of which knowledge work is actually being automated.

These are beginnings. We need much more.

The encouraging part is that almost no one actually wants disaster. Yes, not everyone is pulling in exactly the same direction, but no one is actively trying to destroy the world. Markets, politics, and nations are complex adaptive systems, full of forcing functions and inversions that can swing the whole thing toward a better path.

So what can each of us actually do? The most powerful thing is also the most accessible: become informed, and get everyone around you informed too. Most people have genuinely no idea what is happening. The social and political engine turns on awareness, and the more people understand the upside and the path, the better the odds of a majority demanding the right changes. Every conversation you have with a friend, a family member, or a colleague about the real possibilities of this transition shapes the collective understanding that makes political action possible. Share articles and videos. Leave thoughtful comments. Follow, subscribe and amplify the researchers, economists, and writers working seriously on AI’s positive impact. If you create content, use it to talk about these possibilities. If you’re politically engaged, write to your representative, show up to town halls, and ask candidates directly what their position is on AI and economic security. Most politicians are not yet acting on this. Confronting them with the question is what changes that.

The window for shaping this transition is open right now. It won’t stay open indefinitely. The question isn’t whether AI will reshape the economy. The question is whether we’re having the right debates and taking the right actions to build the new societal infrastructure in time.

The Veil Is About to Lift

We think of ourselves as an advanced civilization. In some respects, we are. But look honestly at what still defines ordinary human life in 2026: the daily anxiety of economic precarity, diseases we still can’t cure, resources distributed with grotesque unfairness, wars fought over scarcity, and entire populations trapped by circumstances they had no hand in creating. These aren’t the hallmarks of an advanced civilization. They’re the marks of one still constrained by limits so old we’ve stopped seeing them as limits.

The root cause of most human suffering has always been scarcity: of resources, of healthcare, of opportunity, and above all, of intelligence. The intelligence required to solve our hardest problems has always been the bottleneck. We’ve never had enough trained, focused minds to tackle everything that needed solving.

That constraint is lifting.

I understand why the scale of this future sounds impossible. The changes are monumental, overwhelming in size and scope, too big to hold in your head. But abundance is not sci-fi magic. It is energy, automation, intelligence, and matter, rearranged at scale.

The pessimists who insist we slow down are reasoning from inside the old scarcity mindset. They fear that a civilization many times richer would somehow exhaust the planet, when abundant intelligence points firmly the other way. The old world was built by scarce human genius. The next one will be built by endless synthetic genius, and that points toward Star-Trek-level wealth and technology arriving in the 2030s.

Slowing down also carries a terrible cost that is easy to forget. Every single day, around 150,000 people die from causes that advanced AI has a clear path to addressing, from inadequate diagnostics to drugs developed too slowly to accidents that autonomous systems could prevent. Of those, 25,000 die of hunger, in a world that already grows more than enough food for everyone.

We cannot afford to stop. What we can afford, and what we must insist upon, is that the transition is built with every person’s dignity and security taken seriously. Degrowth will not save us. It only makes people poorer, slows innovation, and traps civilization in managed decline. Every great leap in human history came from building more, discovering more, and becoming more capable, so the way forward is acceleration with a conscience.

We stand at a genuine crossroads, with a dark path and a bright path in front of us. The bright one is a world where nobody goes without, where nobody gets sick, where nobody is abused, where AI and robots handle the surviving so that humans can get on with the living. Reaching it requires us to wake up and demand that governance change, that governments serve their people and that companies serve their societies.

I cannot sit still through a moment like this. The main thing standing between most people and hope is simply that nobody has told them what future is possible. That is why I write my articles every week.

I am optimistic for a simple reason. We are standing at the edge of the greatest transformation in human history. For almost all of civilization, people lived inside hard walls, disease, poverty, physical weakness, short lives, slow knowledge, and exploitative labor. Those walls are finally starting to crack.

The world is still messy, but the direction is unmistakable. We are moving toward something vastly larger and more beautiful than anything our species has built before. A world where survival is no longer the price of existing. A world where we can finally be human, in the fullest sense of the word.

Stand up for this future. Demand it. The window is open right now.

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Shout-out to David Shapiro, David Scott Patterson and Dr. Alex Wissner-Gross for inspiring my work and providing profound groundwork that found its way into this article.

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AI is changing our world fast. We can only steer this change in the right direction if we understand it. My mission is to educate as many people as possible. If you found value in this, please share it with friends and family to help them get informed.