An Inconvenient Truth About AI

Rutger Bregman

Jun 07, 2026

Hey everyone! I don’t say this often, but I think this is the most important thing I’ve published in quite some time. Watch it as a video essay or read it below. I think we're sleepwalking through the most important shift of our lifetimes, and the people who should be sounding the alarm are looking the other way. If you agree, please share it widely.

If you’re old enough, you may remember this moment.

It’s 2006. Former presidential candidate Al Gore presents the documentary An Inconvenient Truth. Behind him, there’s an enormous screen that shows the level of CO2 in the atmosphere going back hundreds of thousands of years. He walks the audience through it, ice age by ice age. And then, to show where the line will be in fifty years, he climbs onto a scissor lift and rises.

Within two years, Al Gore has won an Oscar and a Nobel Peace Prize. For one brief moment, it feels as though the world might finally listen.

But we all know what happened next. The climate deniers mobilized. They brought a snowball onto the Senate floor and asked, where’s your global warming now? They said things that were technically true (like CO2 is good for plant growth) and completely misleading. And above all, they moved the goalposts.

First it was: the climate isn’t warming. Then it became: fine, it’s warming, but not because of us. Then it was: okay, it’s us, but it won’t be that bad. Then it became: alright, it’s pretty bad, but… it’s China’s fault and we can’t afford to fix it.

The whole time, Al Gore’s red line kept climbing.

I was 18 years old in 2006, and I was furious. How could any serious person look at this evidence and refuse to see it? Climate denial, I thought, was a disease of the right.

And you know what? I was wrong. Not about the right, but about who else is capable of denial. Because we, the liberals, the left, the journalists, the academics, the 97% ‘In this House we Believe that Science is Real’ crowd, we are now doing to the threat of artificial intelligence exactly what the right did to the threat of climate change.

The deniers are us.

Part 1: The Denial

In March 2023, The New York Times published an op-ed by Noam Chomsky: one of the most prominent intellectuals alive and a hero of my political tradition. The piece was called The False Promise of ChatGPT. Chomsky argued that AI is incapable of real thought and that treating them as intelligent was a basic mistake. He called them a ‘lumbering statistical engine for pattern matching’.

This was the consensus of a lot of serious people. The New Yorker ran a long essay arguing that ChatGPT was a blurry JPEG of the web, a lossy compressor that memorized the internet badly and hallucinated the rest. In 2021, the linguist Emily Bender and the computer scientist Timnit Gebru had given this whole skeptical movement its slogan: these machines, they wrote, are stochastic parrots. They just imitate.

Chomsky, Bender, Gebru are smart people. And yes, some of what they have warned about has come true. The web is drowning in machine-generated slop, the training data is biased and the energy bill is pretty staggering. But their central conviction, that this whole Silicon Valley AI-project would hit a wall any minute now, that conviction has completely collapsed.

In the three years since those pieces were published, here’s a partial list of things that the “stochastic parrot, blurry JPEG, lumbering pattern-matcher” has done:

It has won art and writing prizes without the judges knowing it was a machine they were judging.

It has passed the medical licensing exam, and out-diagnosed doctors in head-to-head studies.

It has run the first clinical trial of an AI therapist, and halved the depression symptoms of patients in eight weeks.

It has won a gold medal at the International Mathematical Olympiad. It has cracked maths problems that had stumped researchers for decades.

It has outscored PhDs answering questions in their own field, questions designed so you cannot Google the answer.

And perhaps most importantly: this supposedly stupid parrot is improving itself now. Inside leading AI labs, more than 90% of the code is currently written by AI.

But of all the data, here’s the chart that captures the AI revolution most clearly:

Source: AI Digest.

There is a research group called METR. Since 2019, they have measured something simple: how big a coding task can an AI complete on its own? And they measure that ‘bigness’ in human time, meaning: how long would it take a skilled human to do the same task?

In 2022, the answer was about 30 seconds. In 2023, it was 4 minutes. In 2024, it was 40 minutes. In 2025: 6 hours. And earlier this year, 12 hours.

At this moment, AI capabilities are doubling every 3 months.

So to be honest, I think this METR graph is even scarier than the CO2 graph Al Gore showed us. Because this line is climbing far steeper. Here, ‘off the charts’ is not 50 years away, but 5 years away.

Source: AI Digest.

I’ve personally never written a line of code in my life. But in the past few months, I’ve let AI build me whole apps, websites, dashboards and even a voice-controlled teleprompter app I used to record the video version of this essay. Multiple times a week, I have what I can only call WTF-moments. Especially in the last 6 months, the gap between what these systems can actually do and what most people assume they can do has just kept widening.

For example, I think AI is actually pretty good at writing. Sure, there’s a huge amount of machine-generated slop on LinkedIn (and Substack?), but as Benjamin Todd recently wrote:

Plastic surgery is most noticeable when it's bad, so it's more widespread and successful than it looks. Same with AI writing.

Sometimes I want to shake people: have you actually used it?! Many skeptics seem to have opened ChatGPT in 2023, asked it to write a limerick, watched it fumble, and closed the tab. Well, that was three years ago. Three years in AI is a geological era. Judging today’s models by GPT-3.5 is like judging smartphones by a 2007 BlackBerry.

To be fair, I think journalists deserve much of the blame. The people whose job it is to report on the most newsworthy events have often ignored it. For example, the day the leading AI-lab Anthropic announced Mythos (an insanely powerful model capable of hacking anything from power grids to water systems) it didn’t even make the front page of a single major news site. The Guardian decided a Vogue cover with Anna Wintour and Meryl Streep was more important.

Part 2 : The Largest Infrastructure Build-out in History

Meanwhile, the AI-race is speeding up. Remember: the models of today are the worst models we will ever have. From here on, they’ll only get more powerful.

And honestly, I think it’s hard to wrap your head around the scale of what’s coming.

Look at the first line of this graph. That’s what the companies have spent on AI data centers since 2019, and what they’ve got planned for 2026. To be clear: this is the largest capital build-out in the recorded history of our species. It’s larger than the interstate highway system. Larger than the International Space Station. Larger than the Moon Landing and the Manhattan Project combined, and it is not even close.

Source: Fin Moorhouse.

Mark Zuckerberg’s Meta is currently building a single data center in Louisiana that, when finished, will cover nearly four times the size of Central Park. Amazon is spending more on data centers in one year than the entire annual defense budget of Germany. Microsoft, Google, Meta and Amazon will spend three times as much on AI infrastructure in 2026 than the entire Marshall Plan that rebuilt Europe after the Second World War.

But isn’t it all a bubble?

That is the next move the deniers make. Once “it’s just a silly parrot” stops working, they fall back to: it’s financial madness. The data centers are serving no real demand. It’s all hot air, or even a deliberate scam.

And to be fair, the skeptics have some ammunition. A viral MIT study published last year found that 95% of corporate AI pilots deliver zero measurable returns. The company Klarna replaced 700 customer service workers with AI, then quietly rehired humans because customers couldn’t stand talking to the bot. McDonald’s killed its three-year AI drive-thru experiment after the system kept putting bacon on ice cream.

But you know what? None of this proves anything. Let me show you why.

First, look at user growth. It took Instagram 2.5 years to reach 100 million users. At the time, that was the fastest growth story ever recorded. For comparison: ChatGPT hit that milestone in 2 months. Fifteen times faster.

Next, let’s look at revenue, and at one AI-lab in particular: Anthropic. Here is its annualized revenue, month by month:

January 2025: 1 billion dollars. May: 3. June: 4. August: 5. October: 7. December: 9 February: 14. March: 19. April: 30. May: 45

Source: Sherwood News.

That’s right, 45 billion dollars in annualized revenue. From one company. Up 44-fold in 15 months. No company in any era – not Rockefeller’s Standard Oil, not Microsoft at the dawn of the personal computer, not Google in the tech boom – nobody ever has scaled revenue this fast. We’re talking about the fastest-growing company in the history of capitalism.

So, if this is really such a useless and fraudulent bubble, then why are people paying so much money for it? Why is the demand for AI rising faster than companies are able to build data centers? Why are IT departments, in the words of a Goldman Sachs analyst this April, overrunning their AI budgets “by orders of magnitude”?

I’m sorry to say it, but there’s a lot of highbrow misinformation circulating in left-wing media about AI. Take that viral MIT report. Read it carefully and you see the headline got it backwards. The “95% failure rate” includes the 80% of companies that never piloted any AI in the first place. As the podcaster Rob Wiblin pointed out in a careful breakdown of the study, this is like saying 95% of Tinder users have failing marriages, when most of them have never been on a date. Among the companies that actually deployed AI, about a quarter succeeded within six months. And the study’s own data shows that more than 90% of workers at those companies are using ChatGPT or Claude regularly at work, often multiple times a day.

This should not be surprising at all. If you know how to use it, this technology is already very, very useful, and it will only get more so. But if you don’t use it (perhaps because you work at the DNC, which has barred its staffers from using Claude and ChatGPT) then yes, you become particularly prone to misinformation about it.

Sure, some AI companies are probably overvalued. And yes, some will fail. I think OpenAI is particularly vulnerable. But here’s what the bubble-callers keep missing: even if half of them go bust tomorrow, the infrastructure stays. The data centers, the chips, the models and the capabilities stay.

The railway bubbles of the nineteenth century ruined lots of investors. They also created a rail network that powered the Industrial Revolution, the tracks of which still carry trains today. I actually don’t think this AI build-out is a bubble, but even if it is, remember: bubbles build infrastructure. Bubbles build the future. And a bubble of this magnitude, bursting tomorrow, would still leave us with a civilization permanently reorganized around machine intelligence.

So, ever since 2021, the AI skeptics have been moving the goalposts.

First it was: it’s just a spicy autocomplete machine. A stochastic parrot. A word guessing program. Then it became: fine, it can mimic, but it’ll never reason. Then they said: okay, it can pass the tests, but no serious business is using it. Then: alright, businesses are using it, but the economics don’t add up, it’s one big bubble. Then: fine, the revenue is real, but, but, but…

And this whole time, the line kept c

[truncated for AI cost control]