The Abundance Question

What superintelligence actually asks of us — and why the answer isn't about jobs

We are arguing about the wrong thing.

The debate of the moment is whether AI will take the jobs. Every week brings a new forecast — McKinsey says thirty percent of US work could be automated by 2030, Gartner says AI will create more roles than it destroys by 2027, Sam Altman says even the CEO's job isn't safe, and somewhere a chief economist insists people will always pay extra for the human touch. Each camp marshals its data. Each is partly right. And all of them are circling a smaller question while the larger one sits untouched in the middle of the room.

The larger question is not will we work. It is who are we when we don't have to.

That question is old. What's new is that we may finally be forced to answer it.

The promise, stated plainly

Strip away the theatrics and the abundance thesis is genuinely staggering.

If intelligence becomes as cheap and plentiful as electricity — and that is the explicit bet of every major lab — then the cost of producing most goods and services trends toward zero. Disease becomes a solvable engineering problem. Scientific discovery compounds at machine speed. The material scarcity that has defined every society in human history, that has driven every war and structured every economy, could in principle end.

This is not a fringe claim anymore. It is the stated objective of the most capitalized companies on earth. When Elon Musk says saving for retirement won't matter because abundance is coming, he is not being whimsical. He is describing the world his companies are built to produce.

So let's take the promise at face value, more seriously than its champions usually do. Suppose it works. Suppose, within a generation, the economic problem — the one that has organized human life since the first surplus grain was stored — is genuinely solved.

Then what?

The oldest dream, and its hidden trap

We have imagined this before, and the imagining is instructive.

In 1930, in the teeth of the Depression, John Maynard Keynes wrote that his grandchildren would work fifteen hours a week. Rising productivity would solve scarcity, and humanity would face what he considered a more profound challenge than any economic one: how to occupy a freedom that no prior generation had known. He called it the permanent problem of the human race — learning to live wisely, agreeably, and well.

Keynes was right about the productivity. We are vastly richer than his era. He was almost entirely wrong about the fifteen-hour week.

Why he was wrong is the part that matters now, because the same trap is set for us. As fast as technology eliminated old necessities, we manufactured new ones. The phone became a need. Then the better phone. Our definition of "enough" expanded to consume every gain in productivity, leaving us exactly as busy as before, running on what one writer called a hamster wheel we cannot step off.

Here is the uncomfortable insight: scarcity did not simply trap us. On some level, we chose it. Faced with the possibility of enough, we redefined enough upward. We kept working not because survival demanded it but because work had become the scaffold we built our identities on, the answer to the question we ask strangers within minutes of meeting them. What do you do?

Superintelligence threatens to remove that scaffold whether or not we are ready to stand without it. And this time the productivity gain may be too large to absorb through invented wants. You cannot manufacture enough new needs to keep eight billion people busy if intelligence itself — the thing we sold in the labor market — has become a commodity.

Three futures, and none of them are clean

When I try to think honestly about where this goes, I don't see one future. I see three, braided together, and our task is to bend the mix toward the better strands.

The first is hollow abundance. Material needs are met. Universal basic income, or something like it, arrives. And a large share of humanity discovers that a life without necessity is not the same as a life with meaning. We already have a preview: surveys find a meaningful fraction of young workers consider their jobs meaningless, and the early data on a generation raised by screens is not reassuring. Remove struggle entirely and you do not automatically get flourishing. Sometimes you get drift, anomie, and the peculiar despair of people who have everything to consume and nothing to build. Abundance is necessary for the good life. It is nowhere near sufficient.

The second is a new stratification. Abundance arrives, but unevenly, and the fault line is no longer who owns capital but who owns purpose. A minority — those with the inner resources, education, and temperament to author their own meaning — flourish extraordinarily, freed to create and explore as only aristocrats once could. The rest are pensioned into comfortable irrelevance, materially provided for and existentially adrift. This is perhaps the most likely path, and the most quietly dystopian, because it wears the mask of generosity. A society can feed everyone and still waste most of them.

The third is a renaissance. Freed from survival labor, humanity pours its energy into the things machines cannot do for us because the doing is the point — the philosopher Hannah Arendt's distinction between labor (what survival demands), work (what we create), and action (how we engage one another and the world). Abundance dissolves labor and liberates the other two. Art, inquiry, care, craft, the deepening of relationships, the asking of questions that have no commercial use. Value migrates toward what is rare, and in a world of infinite copies the rarest thing is the authentically human. We become, paradoxically, more human as the machines become more capable.

I want to be clear: I don't think one of these simply wins. The future will be a blend, and the blend is not fixed. Which strand dominates depends on choices we are making right now, mostly without realizing they are choices.

The question hiding under the question

Notice what all three futures share. The technology is roughly the same in each. What differs is us — our institutions, our values, what we decide a human life is for.

This is the thing the jobs debate misses. We keep asking whether the machines can do the work, as though that were the cliff edge. But the machines doing the work was always going to happen. The real edge is whether we have prepared a conception of human worth that does not depend on economic usefulness — because for the entire history of the modern world, we have not had one. We have measured a life largely by its productive contribution. We built an ethic around the dignity of work and then forgot it was a story we told, not a law of nature.

Superintelligence calls that story's bluff. If a machine can be a better CEO, a better doctor, a better researcher — Altman's own concession — then a worth grounded in output collapses for nearly everyone, nearly at once. The accountant and the executive find themselves in the same boat, and it is a boat we have never had to sail before: a world where being economically necessary is no longer the basis of being valued.

We will need a new answer to what is a person for. And we are dangerously unprepared, because we outsourced that question to the labor market generations ago and stopped asking it ourselves.

What I actually believe

I am an optimist, but not the cheap kind. The cheap optimism says the technology will sort it out. It won't. Technology has never once handed us meaning; it only ever clears the ground on which we must build it ourselves.

The honest optimism is harder. It says abundance is worth wanting and it will expose us, mercilessly, for how little we have thought about what we'd do with it. A civilization that has organized itself around scarcity for ten thousand years does not gracefully pivot to flourishing the morning scarcity ends. The muscles of meaning-making — community, ritual, craft, the patient cultivation of a self not for sale — have atrophied in exactly the era that is about to need them most.

So the work ahead is not technical. The labs will deliver the capability; that part now looks close to inevitable. The work ahead is human, and it is this: to rebuild, before we need it, a sense of human worth that can stand on its own without an economic crutch. To raise people who can author their own purpose rather than receive it from an employer. To design institutions that distribute not just income but meaning — access to the kinds of work, in Arendt's sense, that make a life feel like it was lived rather than merely funded.

That is a harder project than building the AI. It cannot be solved by a model. It has to be chosen, repeatedly, by a society that decides on purpose what it wants to become.

The question we should actually be asking

So I'd retire the jobs debate, or at least demote it. Will AI take the jobs is a question about the next five years. The question about the next fifty is the one Keynes left us and we never answered:

When the struggle for survival ends, what is a human life for?

The machines are forcing the question into the open, sooner and harder than any philosopher managed to. That may turn out to be their greatest gift — not the abundance itself, but the way it drags us, finally, into asking what we are for, and refusing to let us look away.

The future of society won't be decided in the data centers. It will be decided in whether we use the freedom they create to become more fully ourselves, or simply more comfortably empty.

We get to choose. We just have to notice that we're choosing.

This is the kind of question we keep returning to on Masters of Automation — not whether the technology works, but what it asks of us once it does. If that's your kind of question too, the newsletter is where the thinking continues.

Founder, Alp Uguray

Alp Uguray is a technologist and advisor with 5x UiPath (MVP) Most Valuable Professional Award and is a globally recognized expert on intelligent automation, AI (artificial intelligence), RPA, process mining, and enterprise digital transformation.

https://themasters.ai
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