I was reading about China and Taiwan when I found myself stuck on a very simple question:

Why?

Not why does China want Taiwan. I understand the history. Civil war. Sovereignty. Territorial integrity. National identity. A century of competing claims compressed into words like reunification.

I mean: why are we still doing this?

Nearly 24 million people live in Taiwan today. They work, fall in love, raise children, build companies, vote, argue about politics, and plan what they’re doing this weekend. Almost none of them had anything to do with the Chinese Civil War.

Neither did almost anyone living in China.

Yet here we are, three generations later, contemplating the possibility that enormous numbers of living people could someday be asked to fight and die over an argument they inherited.

And Taiwan is hardly unique.

Look around the world and you begin to notice how much of civilization consists of inherited arguments.

Borders drawn by people who are dead.

Religious conflicts started by people who are dead.

Territorial claims based on governments that no longer exist.

National enemies inherited from our grandparents.

Political institutions designed for technologies, economies, and societies that would be almost unrecognizable today.

We inherit these things so completely that eventually we stop recognizing them as choices.

They become reality.

But reality keeps changing.

And something else has changed that I don’t think we fully appreciate yet: our ability to understand one another.

For most of human history, where you were born largely determined what you knew about the world. Your parents, teachers, community, religion, and government supplied much of the framework through which you understood it. Your language constrained what you could read. Geography constrained whom you could meet. Traveling halfway around the planet was something most humans would never experience.

Even curiosity had practical limits.

Imagine being sixteen years old in 1965 and wondering why Israelis and Palestinians both believed the same piece of land belonged to them. Or what life was actually like in China. Or why India and Pakistan hated each other. Or whether the version of history taught in your classroom was the same version being taught somewhere else.

You could ask someone. You could find a book. Maybe you had an exceptional teacher. Maybe someday you would travel there.

Or, much more likely, the question would simply pass.

That’s profoundly different from growing up today.

A curious teenager can wonder about something, pull a phone from their pocket, and have an answer in seconds. That answer can produce another question, which produces another answer, which produces another question.

Curiosity no longer has to wait.

And that matters because curiosity compounds.

One answer connects to another. History connects to economics. Economics connects to geography. Geography connects to religion. Religion connects to culture. Suddenly something that once looked like an incomprehensible conflict between strangers on the other side of the planet becomes a story involving actual human beings whose motivations, fears, and histories you can begin to understand.

The internet started collapsing that distance.

AI is collapsing it further.

Not because AI has the answers to humanity’s problems. It doesn’t. And not because having more information automatically makes people wiser. It clearly doesn’t.

What’s changing is the friction between curiosity and understanding.

A language you don’t speak is becoming less of a barrier. An academic subject you never studied is becoming less inaccessible. A perspective you’ve never encountered can be explored rather than merely dismissed. You can ask the stupid question, then the better question, then the uncomfortable question, without needing an appointment with an expert or worrying about revealing how little you know.

For someone whose brain is still forming its picture of the world, that is an extraordinary environment in which to grow up.

Previous generations didn’t have that advantage.

That isn’t an indictment of them. A person born in 1945 was no less intelligent or curious than someone born in 2005. But intelligence operates on the information available to it. Much of the worldview of older generations was formed when information was scarce, geography mattered enormously, cultures were comparatively isolated from one another, and challenging the accepted version of events required considerably more effort than opening another browser tab.

Those formative frameworks can persist long after the environment that produced them disappears.

And institutions persist even longer.

Governments, corporations, religions, political parties, and nations accumulate beliefs in much the same way people do. Eventually nobody remembers exactly why something must be done a particular way. There is simply a policy, a border, an alliance, an enemy, a tradition.

We inherited it.

So we continue it.

Perhaps this is one reason our technology can feel as though it belongs to the future while our politics so often feels trapped in the past.

We are becoming globally connected faster than our institutions are becoming globally minded.

A twenty-year-old today can play a video game with someone in Seoul, watch a Ukrainian describe her morning on social media, learn physics from an Indian professor, follow a Nigerian entrepreneur, translate a conversation with someone in Tokyo, and ask an AI to explain why China believes Taiwan belongs to it.

Borders remain politically powerful.

But they are becoming intellectually porous.

And perhaps that matters more than it initially appears.

Because once you understand people on the other side of a border, it becomes harder to reduce them to the abstractions necessary to sustain inherited conflicts.

They stop being the Chinese, the Russians, the Israelis, the Palestinians, the Americans.

They become people.

People who mostly want remarkably similar things: security, opportunity, dignity, family, some control over their lives, and the chance to leave their children something better.

None of this means history doesn’t matter.

It matters enormously.

Nor does it mean everything old should be discarded. Much of what previous generations built is extraordinary, and civilization depends upon accumulated knowledge.

But perhaps inheritance should come with an expiration date.

A border can have a history without having a destiny.

A grievance can be remembered without being reenacted.

A culture can preserve its identity without requiring another culture to surrender its own.

And a generation can respect the world it inherited without agreeing to keep running it exactly as it was handed to them.

Maybe the most consequential thing about our increasingly connected world isn’t that we’re finally able to know what everyone else thinks.

It’s that we’re becoming capable of asking something our ancestors rarely had the opportunity to ask:

If we were designing the world today, knowing what we know now, would we build it this way?

And if the answer is no, how long are the dead entitled to keep voting?

The other day I found myself copying a response from one AI and pasting it into another AI.

Then copying that AI’s response and pasting it back into the first one.

Then back again.

At some point I realized what I was doing.

I was middleware.

Two remarkably capable artificial intelligences were having a conversation, and apparently the communications protocol between them was me.

This seemed inefficient.

It started with my phone bill

I was considering switching from Verizon to T-Mobile.

Not exactly civilization-changing stuff, but there were enough variables to make it complicated. I still owed money on my iPhone. T-Mobile had an offer to reimburse some of that if I switched. There were different plans, different promotions, an Apple Watch sharing my number, AutoPay discounts, trade-in offers, eligibility periods, and various rules about which things could be combined.

So I started asking AI to help me sort it out.

And it was remarkably good at it.

I wasn’t just asking, “Which plan is cheaper?” I was giving it four or five things to figure out at once. Compare these plans. Include the watch. Account for what I still owe Verizon. Figure out whether this $800 switching offer can coexist with that phone promotion. Tell me what happens if I wait 90 days. And while you’re at it, tell me if there’s something I haven’t thought to ask.

The answers came back almost immediately.

That part is easy to overlook.

Give the same problem to a human representative and they would have to understand the whole thing, look up several policies, keep all the dependencies straight, probably put me on hold at least once, and then explain it back to me.

I’m not even sure I could have gotten the same level of analysis from a human, no matter how long I was willing to stay on the phone.

But there was another problem.

One AI knew what Verizon was doing. Another knew what T-Mobile was offering. And neither could talk to the other.

So I copied.

And pasted.

And copied.

And pasted.

It was like having two brilliant attorneys negotiating a contract while I stood between their offices carrying handwritten notes.

Except the attorneys could think in milliseconds.

And I was using Command-C.

Why am I in the loop?

Once I noticed it, I started wondering why I was involved at all.

My AI already knew what I wanted. It knew what I was paying, what devices I had, what mattered to me, and what questions needed to be answered.

T-Mobile’s systems presumably knew what T-Mobile could offer.

Why couldn’t they just work it out?

My AI could say: Mateo wants to keep his phone and number, keep his Apple Watch working, preserve or improve his service, eliminate as much of his remaining device balance as possible, and lower his monthly bill. Here are the constraints. What can you do?

T-Mobile’s AI could respond.

Mine could challenge something.

Theirs could counter.

Maybe Verizon’s AI gets involved and decides it would rather keep me.

Fine. Let them fight.

Wake me when somebody wins.

Instead, we’ve built systems capable of reasoning through the entire transaction and left the human responsible for moving the text between them.

That feels temporary.

Then I started noticing how much middleware I actually do

Phone service is probably the least interesting example.

Why am I comparing insurance policies?

Why am I watching for subscription increases, remembering to cancel free trials, negotiating internet bills, finding flights, filling out the same information on forms, scheduling appointments, submitting warranty claims, disputing charges, and tracking packages?

None of these things is particularly difficult.

But collectively, we’ve turned every functioning adult into the unpaid operations manager of a small organization consisting of themselves.

A surprising amount of modern life is administration.

And we’ve spent decades trying to make that administration more efficient.

We went from offices to phone calls, from phone calls to websites, from websites to apps, and now from apps to AI.

But I’m still here.

Clicking things.

Remembering things.

Moving information from one system to another.

Being middleware.

Presumably this goes away

The obvious next step isn’t a better chatbot.

It’s giving the chatbot permission to do things.

And we’re already starting to see the next step. Grok Bot, for example, gives an AI its own computer and lets it work across applications, completing jobs end to end instead of waiting for a human to shuttle information between them. In other words, somebody at xAI apparently noticed my new career as middleware and is already working on eliminating the position.

If my AI knows that I want the least expensive cellular plan that meets a certain set of requirements, why should I shop for it?

Go shop.

Negotiate.

Come back when you have something worth showing me.

Maybe it says:

T-Mobile will save you $37 a month. They’ll reimburse $800 of what you owe Verizon. Your watch will still work. You’ll lose one feature you don’t use and gain international data. Switching will cost you $214 after everything settles.

Do you want me to do it?

Sure.

Eventually, even that question might be unnecessary.

I could give it rules.

You may change recurring services without asking me if you save at least 10 percent, don’t reduce the quality of the service, don’t create a commitment longer than a year, and don’t spend more than $500 in the process.

Now my phone plan changes while I’m out riding my bike.

That seems better.

Although there may be a problem with where this leads

I’ve spent a large part of my career making things more efficient.

Fewer steps. Less labor. Less waiting. Less duplication. Fewer opportunities for somebody to screw something up.

That’s usually considered progress.

But if you keep following that logic, eventually you arrive at a strange place.

What happens when we’ve streamlined almost everything?

Not just phone plans and insurance forms. Work itself.

I’ve written about the larger version of that question before, in When Nothing Needs to Be Done: what happens if intelligence and labor become abundant enough that much of the work required to sustain our lives simply isn’t necessary anymore?

This is a much smaller version of the same question.

Maybe we don’t wake up one morning and discover that the robots have taken all the jobs.

Maybe things just start disappearing.

First I stop calling the phone company.

Then I stop comparing insurance.

Then I stop booking flights.

Then I stop paying bills, filling out forms, scheduling appointments, renewing things, canceling things, negotiating things, and keeping track of all the little administrative debris that seems to accumulate around being alive.

Good.

I don’t think most of us will mourn the loss of hold music.

But then what?

For thousands of years, we’ve spent an enormous percentage of our lives doing things because they needed to be done.

For many people, nearly all of life is still organized around survival.

If we actually succeed at removing more and more of that necessity, maybe the question stops being how to make everything more efficient.

Maybe it becomes what all that efficiency was for.

Art. Travel. Learning things for no reason. Building things because they’re interesting. Spending time with people we like. Sitting by the ocean.

Doing absolutely nothing.

We’ve spent an extraordinary amount of effort trying to save time.

It would be funny if the thing we’re least prepared for is actually having it.

But we’re not there yet.

For now, the machines are apparently waiting for me.

Command-C. Command-V.

I was going through my Verizon bill recently, trying to figure out exactly what I was paying for and whether I could consolidate it without giving something up. Somewhere in the process I came across yet another feature available for another monthly charge.

The amount itself was trivial. What bothered me was the familiarity of it. It seems like everything now comes with a monthly fee attached.

I pay Apple every month for storage. I pay Google every month for my security cameras. I recently bought a used Eight Sleep system, only to discover that some of the intelligence that makes the thing interesting requires a subscription. Software I once would have purchased now generally requires a monthly or annual payment. Streaming services have multiplied to the point where replacing cable with streaming can involve half a dozen separate bills.

None of these expenses is particularly outrageous on its own. That’s probably why the model works so well. But I started wondering what happens if we keep going in this direction.

Does everything eventually become a subscription?

It’s an especially strange question to consider at this particular moment because technology seems to be pushing us in precisely the opposite direction.

Things should be getting cheaper

One of the recurring themes I’ve been thinking and writing about is the possibility of abundance.

AI is already making certain kinds of intellectual work dramatically less expensive. Robotics should eventually do something similar for physical labor. Add increasingly cheap energy, automated manufacturing, better materials and recycling, and it’s not difficult to imagine the actual cost of producing many goods and services falling substantially over the next decade or two.

That’s not a particularly radical prediction. Technology has been doing this for a long time.

Computing is the obvious example. The amount of computing power and storage available to an ordinary person today would have been unimaginably expensive a few decades ago. Communication that once cost dollars per minute can cross the planet essentially for free. A phone in your pocket replaced a camera, GPS receiver, music player, calculator, flashlight, encyclopedia and quite a few other things people once bought separately.

AI and robotics could extend that process much further. If machines eventually perform a large percentage of both intellectual and physical labor, labor stops being the major component of the cost of many things.

That line of reasoning is what led me to write about post-scarcity in the first place.

But the Verizon bill made me notice another possibility I hadn’t thought much about.

What if the cost of producing things keeps approaching zero, but the cost of accessing them doesn’t?

We used to buy things

I remember buying software in a box.

You paid for it once, installed it on your computer and used it until you decided there was enough value in the next version to buy it again. The software company had to convince you that the upgrade was worth paying for.

Subscriptions changed that relationship.

For businesses, the appeal is obvious. Selling something once produces revenue once. Turning the same customer into a subscriber produces predictable revenue every month, potentially for years. Investors like predictable recurring revenue, companies like it, and apparently consumers will tolerate quite a lot of it.

So the model spread well beyond software. Music, movies, news, cloud storage, security systems, exercise equipment and increasingly the capabilities of physical products themselves can all require ongoing payments.

In many cases, subscriptions make perfect sense. Spotify has to license music and operate a service. Cloud storage requires infrastructure. Software that is continuously being developed has ongoing costs. I’m not arguing that subscriptions are inherently bad.

What interests me is what happens when the model becomes the default.

There is a meaningful difference between buying something and buying continued permission to use something. Ownership eventually reaches an endpoint. You pay for the television, bicycle, camera or computer and then, barring maintenance, you’re finished paying for it.

A subscription has no endpoint.

A strange version of abundance

Imagine a household twenty years from now.

Robotic factories manufacture products using very little human labor. Energy is dramatically cheaper. Materials are efficiently recovered and recycled. Transportation and distribution are largely automated. The actual marginal cost of producing many household products might be extraordinarily low.

You might expect that household to be surrounded by things that cost very little.

Maybe it will be.

But it’s also possible that the refrigerator has a service plan. The household robot has one. The car requires connectivity. The home security system has a subscription. The AI running much of the household has several service tiers. Medical monitoring, entertainment, communications, software and automated services all arrive as small recurring charges.

Nothing seems expensive. It’s $8 here, $15 there, $30 somewhere else.

Yet the household needs thousands of dollars every month simply to keep everything turned on.

That’s an odd kind of abundance.

We would have solved much of the technological problem of scarcity while preserving scarcity economically through control of access.

Scarcity doesn’t have to mean running out of something

This is one of the things the digital economy has made particularly clear. Scarcity can exist even when supplying one additional customer costs almost nothing.

A software feature can already exist on a device you own and remain unavailable until you pay to activate it. The additional cost to the manufacturer of letting you use that feature may be effectively zero. What you’re paying for isn’t production. You’re paying for permission.

Again, that doesn’t automatically make the arrangement unreasonable. Someone paid to develop the software. Companies need to make money, and intellectual property has value even when reproduction is cheap.

But carried far enough, it changes the nature of ownership.

A person can own a house filled with sophisticated technology while having surprisingly little permanent access to the capabilities inside it.

And that becomes much more consequential when income is interrupted.

In an ownership-heavy economy, losing your job means you stop buying new things, but most of the things you already purchased continue working. Your television still turns on. Your tools are still in the garage. Your car still drives. Your music collection doesn’t disappear.

In a heavily subscription-based economy, financial trouble could progressively shut down pieces of your life. One service expires, then another, then another.

You don’t necessarily lose your possessions. You lose what they can do.

AI makes the contradiction harder to ignore

This is where the question connects back to the larger technological transition.

AI may make enormous amounts of intellectual labor inexpensive enough that services once available primarily to businesses or wealthy individuals become accessible to almost everyone. Personalized tutoring, sophisticated financial analysis, software development, research, design and other expertise could become extremely cheap.

Robotics could eventually bring the same economics into the physical world.

If that happens, it should create an extraordinary amount of abundance. But I’ve probably been too quick to assume that falling production costs necessarily translate into falling costs for consumers.

They often do, especially when competition is strong. But they don’t have to.

If a small number of companies control the systems producing that abundance, the important economic question may not be how cheaply something can be produced. It may be how much people are willing to pay for access to it.

In other words, a world capable of producing abundance isn’t necessarily the same thing as a world in which abundance is broadly available.

You can put a tollbooth in front of something that is plentiful.

Maybe the model eventually breaks

There are good reasons to think this won’t continue indefinitely.

When technologies mature and competitors multiply, margins tend to collapse. Open-source AI can compete with subscription services. Household robots could eventually become appliances you simply own. Distributed energy may allow people to produce more of their own power. Manufacturing itself may become smaller, cheaper and more local.

Consumers also have limits. There are only so many recurring charges people can absorb before they begin actively avoiding them.

So perhaps the proliferation of subscriptions is just a feature of this stage of the technological transition. Companies have discovered an extremely effective business model, and they’re applying it everywhere they can until competition or consumer resistance forces something different.

I don’t know.

But that’s what struck me while staring at a cellular bill and wondering why yet another feature needed its own monthly charge.

I’ve been thinking about a future in which technology makes scarcity less important. At the same time, I’m watching the present economy become increasingly good at turning ownership into access and access into recurring revenue.

Those two trends don’t fit together as neatly as I had assumed. The question isn’t really whether another $10 subscription is affordable.

It’s what happens when nearly everything is.

For most of human history, life has been organized around scarcity.

Food had to be grown. Shelter had to be built. Things had to be manufactured. Someone had to transport them, repair them, sell them, account for them, and manage the people doing all of that work.

Survival required labor.

We built an economic system around that reality. You contribute something other people value, you receive money in return, and you use that money to obtain the things you need or want.

Money, viewed this way, is more than a medium of exchange.

It is stored freedom.

Enough money means I can decide not to work tomorrow. More money means I can make that decision for longer. It lets me choose where I live, what I do, what risks I take, and how much of my limited time belongs to someone else.

This is one reason people spend so much of their lives trying to accumulate it.

But I’ve been wondering what happens if the assumptions underneath that entire system begin to disappear.

Intelligence is becoming cheap

We’re already watching the first part happen.

A growing amount of intellectual work can now be performed by artificial intelligence. Writing software, analyzing information, creating images, researching subjects, designing systems, answering questions, diagnosing problems, and coordinating increasingly complicated tasks are becoming faster and cheaper.

We’re nowhere near the end of that progression.

Eventually, asking an AI to perform a complicated intellectual task may become about as remarkable as asking a calculator to divide two numbers.

At that point, intelligence itself begins to look less like a scarce resource.

But intelligence is only half of the equation.

The other half is labor.

What happens when robots build robots?

Imagine increasingly capable general-purpose robots that can perform much of the physical work humans currently perform.

They mine materials.

They operate factories.

They build houses.

They grow and harvest food.

They maintain infrastructure.

They manufacture products.

They repair one another.

And eventually, they manufacture more robots.

That last step matters.

A robot that can build another robot changes the economics of labor in a fundamental way.

Today, producing another worker requires roughly two decades of biology, parenting, education, housing, food, healthcare, and social development.

A robotic worker could eventually be manufactured in hours or days.

Then that robot can help manufacture another.

And another.

The productive capacity of civilization would no longer scale primarily with the number of humans willing and able to work.

It could scale with machines.

Then follow the chain one step further

Machines require energy.

But energy is another area where the long-term constraint may look very different from today’s.

The Earth receives an extraordinary amount of energy from the sun. Solar generation, storage, grid technology, nuclear power, and whatever energy technologies emerge next are improving alongside AI.

Machines powered by abundant energy can acquire materials, manufacture products, transport goods, maintain infrastructure, and manufacture more machines.

AI accelerates the science and engineering behind all of those processes.

Better AI creates better machines.

Better machines create more productive capacity.

Greater productive capacity builds more energy infrastructure.

More energy supports more computation and more machines.

The cycle reinforces itself.

This is where the implications become difficult to dismiss as merely “AI taking jobs.”

Jobs may be one of the least interesting consequences.

But what about scarce resources?

This is usually where the argument stops.

There is only so much copper. Only so much lithium. Only so much aluminum. Only so much land.

That’s true if we freeze technology where it is today.

I don’t think that’s a reasonable assumption.

If intelligence becomes dramatically more capable and dramatically cheaper, materials science should advance with it. Recycling should improve. Extraction should improve. Manufacturing should become more precise. Substitution should become easier.

Products may require less material in the first place.

Materials that are expensive or difficult to obtain today may be replaced by materials we haven’t invented yet.

Waste itself becomes a resource if machines can economically disassemble, sort, refine, and reuse it.

And Earth’s resources aren’t necessarily the final boundary either.

The point isn’t that physical scarcity disappears completely. Some things will always be scarce. A particular piece of land can only be occupied by so many people. There is only one original Picasso. There are only so many beachfront homes in Maui.

But most of what humans need to live very well doesn’t require unique objects.

It requires food, energy, shelter, transportation, healthcare, manufactured goods, information, and services.

If the cost of producing those things approaches the cost of energy and raw materials, while both are becoming increasingly abundant and efficiently used, something strange happens.

The marginal cost of a very good life could fall dramatically.

Which raises a more interesting question about ownership

Whenever I think about this future, one objection keeps appearing:

Who owns the robots?

It’s a reasonable question because ownership determines access in the world we currently inhabit.

If one company owns the machines, the factories, the energy systems, and the AI, why would it give everyone else the output for free?

Initially, it probably wouldn’t.

The transition could be messy. Possibly very messy.

But take the thought experiment further.

What happens when machines can manufacture machines, and those machines can manufacture nearly everything else?

The economic importance of owning a particular machine begins to decline if another one can simply be made.

The same applies to factories.

And eventually to much of productive capital.

Ownership is extraordinarily valuable when the thing being owned is scarce.

Abundance changes that equation.

A billionaire today can own ten houses, twenty cars, three airplanes, and a yacht. Those things signal wealth partly because most people cannot afford them.

But if nearly anyone could obtain a beautiful house, excellent transportation, extraordinary food, sophisticated healthcare, and almost any manufactured object at negligible cost, owning more of them becomes considerably less interesting.

You can only sleep in one bed at a time.

At some point, accumulation stops producing much additional freedom because nearly everyone already has access to most of what money once purchased.

That would be a profound change in human incentives.

Money is a bridge

I don’t think money is disappearing next Tuesday.

Quite the opposite.

During the transition, money may become particularly important because our existing economic system will continue operating while the technology underneath it changes.

That’s why I still think of money as stored freedom.

For someone living today, accumulating enough capital provides optionality while we move through a period that could be unusually unpredictable.

But that creates an odd possibility.

We may be spending enormous amounts of our lives accumulating something whose primary purpose is to buy freedom, just before technology begins making many of the things we purchase with that freedom radically cheaper.

That doesn’t make saving money irrational.

It makes the destination interesting.

The goal may not be to become unimaginably wealthy.

It may simply be to have enough resources to cross the bridge.

And then what?

This is the part I find much more interesting than the technology.

Humans have spent essentially our entire existence with survival somewhere in the background.

Even wealthy people organize enormous portions of their lives around work, money, achievement, status, and accumulation.

We go to school so we can get jobs.

We get jobs so we can earn money.

We earn money so we can support ourselves.

We save money so someday we won’t have to work.

Then we call that retirement.

But imagine that sequence becoming unnecessary for most people.

Not because a government sends everyone a check.

Not because wealth has been redistributed.

But because producing the things necessary for an excellent life simply doesn’t require much human labor anymore.

For the first time, a civilization could face a peculiar problem:

What do billions of human beings do when almost nothing needs to be done?

Some people would create.

Some would explore.

Some would compete.

Some would study subjects that have no economic value whatsoever.

Some would raise families.

Some would travel.

Some would build things simply because building them is interesting.

Some would probably spend an astonishing amount of time doing absolutely nothing.

And perhaps we’d discover that much of what we currently call purpose was actually necessity wearing better clothes.

I don’t know whether this happens in ten years or fifty

There are enormous technical, political, economic, and social obstacles between here and there.

Maybe some prove harder than I expect.

Maybe entirely new constraints appear.

But when I look at AI, robotics, energy, automation, materials science, and manufacturing as interconnected systems rather than separate technologies, the direction seems difficult to ignore.

We are steadily reducing the amount of scarce human effort required to produce useful things.

If that trend continues far enough, the question isn’t merely what happens to employment.

It’s what happens to an economic and social system built during a period when human labor was indispensable.

And beyond that is an even stranger question.

For thousands of years, humans have dreamed about freedom from necessity.

We may be among the first generations forced to figure out what to do with it.