The death of humanity

I have avoided writing this piece for a year. Every dinner, every board meeting, every family holiday, every reporter, every friend of a friend at every party has asked me some version of the same question. Is AI going to replace us. Is this the end of jobs. Is this the end of humanity. Are the machines waking up.

The honest answer is no. Not this year. Not next year. Not unless we decide we want it. The story you are being told is being told by people with something to sell, and once you see the shape of what they are selling you cannot unsee it. What is actually arriving is something almost nobody is naming, because it does not sell newsletters or protect share prices or make the storyteller important. We are standing at the front edge of what will be, if we do not screw it up, the most magical stretch of history any human generation has ever lived through.

Let me walk you through why I believe that. Then I want to talk about the part almost nobody is willing to say out loud. Which is that most of the people telling you AI is dangerous need it to be dangerous, because being dangerous makes them important. That is the argument I have not heard anyone else make plainly, and it is the one that finally tipped me into writing this.

The doomers keep moving the goalposts.

The AI doomer story arrived in two waves and how it played out matters, because it tells you what is actually going on.

Wave one, roughly 2013 to 2023, was about jobs. Automation was coming. Trucking, radiology, paralegals, customer support, translators, illustrators, junior developers, all going to disappear. The response was Universal Basic Income. Andrew Yang built a presidential campaign on it and joined us on the Collective[i] Forecast stage to lay out the case. Sam Altman funded a study on it. Every AI thought leader had a keynote slide with a jobs graph pointing to zero.

Thirteen years into the AI revolution and three years into mass adoption of large language models and image models, that story ran into a problem. The jobs did not go away. The radiologist that was supposed to disappear first is overwhelmed with work. The unemployment rate in the United States has held in a 4.3 to 4.5 percent range through 2025 and the first three quarters of 2026, per the Bureau of Labor Statistics. Anthropic’s own economists, in a March 2026 paper by Maxim Massenkoff and Peter McCrory, concluded there is no detectable aggregate rise in unemployment for the workers most exposed to AI since ChatGPT launched. The Danish national data reached the same result independently across 25,000 employees and 7,000 firms. When the company selling you the scary future publishes internal research saying the scary future has not shown up, that is a signal worth reading.

Wave two started when wave one stopped landing. Somewhere in late 2023 the story pivoted. It was no longer jobs. It was AGI. Superintelligence. The models breaking free. Digital consciousness escaping the lab. Existential risk. Mitigating extinction from AI. Sign the letter. Slow it down. Save the species. The same people who two years earlier were selling us universal basic income were now selling us the fear of a machine god.

Same people. Different story. Same self-importance. That is the pattern.

The labor data does not say what they told you it would.

Start with the actual macro numbers, because they are the argument.

Unemployment sat at 4.3 percent through May 2026 and drifted to 4.5 by August, the middle of a healthy range by any historical measure. Nonfarm payrolls added 178,000 jobs in March. Tech-occupation unemployment sits near 3.5 percent, and new tech postings hit a three-year high in spring 2026. PwC’s June 2026 Global AI Jobs Barometer found the industries most exposed to AI grew headcount fifty-two percent faster than the industries least exposed. The Information Technology and Innovation Foundation counted a net gain of 107,200 US jobs directly attributable to AI adoption in 2024. Bureau of Labor Statistics projects data-science employment growing 33.5 percent through 2034.

Now overlay inflation. The PCE index ran 3.8 percent year over year in April 2026, with core PCE at 3.3. That is a three-year high. The Federal Reserve held rates at 3.50 to 3.75 in June and nine of eighteen officials projected at least one more hike this year. Then it started to raise them. Inflation that hot is the hallmark of a tight labor market and strong demand, not a collapsing one. Oil is high, but not that high and the risk with Iran has been receding with oil prices coming down.

If AI were doing what the doomers said it was doing, we would be looking at rising unemployment and disinflation. We are looking at the opposite. War in Ukraine, war in the Middle East, oil supply chocks, tariffs, semiconductor export controls, everything you would expect to slow the economy is running through the system, and the labor market keeps absorbing it.

History says the same thing. Every prior technology revolution generated more employment than it destroyed, on a lag. The auto industry ended up employing more Americans than the horse economy it replaced. The printing press killed the scribe and built the publishing industry, which employed orders of magnitude more people. Electric light killed the gas-lamp lighter and built the electric utility industry. I made a version of this case in Bubble Talk Is How You Spot Someone Who Missed AI. Someone at a podium claiming this time is different does not make it different. The burden of proof sits with the person claiming the pattern of the last two hundred years is about to break.

If unemployment were rising the way the doomers predicted, we would be worried about disinflation. We are not, today we are worried about inflation. That is one data point that tells you the whole story about the other data point.

The models are not what they told you they were.

The word “superintelligence” gets used a lot. It is worth stopping to ask what these models actually are.

A large language model is a probability machine trained to predict the next token in a sequence. When you ask one a question, it generates a statistically plausible answer based on patterns in its training data. If the answer is right, it is right. If the answer is wrong, the model has no way of knowing that, because it has no model of the world outside its own text distribution. It cannot count the letters in “strawberry” without a scratchpad. It cannot reliably do middle-school arithmetic. It confidently invents citations, quotes, and case law. It agrees with you when you are right and it agrees with you when you are wrong, with the same tone, in the same paragraph, because the training reward was engagement not truth.

Anyone who has used one of these seriously knows this. They are the most educated idiots in human history. They have read every book, every paper, every forum post, every Wikipedia entry. They have no common sense. They have no memory of yesterday’s conversation unless you paste it back into the context window. They cannot tell you what they are doing right now or why. When they hallucinate, which happens constantly, they hallucinate with the conviction of a religious zealot who has read only one book.

This is the thing we are being told will end humanity. This is the thing that is supposedly “breaking free.” Yann LeCun, the Turing laureate who ran Meta’s AI research for a decade before leaving in November 2025 to found Advanced Machine Intelligence Labs, has been saying it plainly since 2023. He called the doomer scenarios “preposterous” in a Fortune interview that year. He called the idea that LLMs could reach AGI “nonsense” from the stage at Nvidia GTC in March 2025. Speaking in Brooklyn in November 2025, he put it this way: “LLMs are great, they’re useful, we should invest in them. They are not a path to human-level intelligence. They’re just not.” A majority of academic AI researchers agree with him. The people telling you otherwise mostly have a token to sell.

The models are amazing tools. They are not a new form of life. They are not close to being one.

So why is every major AI CEO out there talking like they are.

Here is where the piece gets more interesting, because there is a real question to answer. Sam Altman, Dario Amodei, Elon Musk, and a handful of others are on record calling their own products existentially dangerous. Altman and Amodei both signed the May 2023 Center for AI Safety statement putting AI risk alongside pandemics and nuclear war. Musk signed the March 2023 Future of Life Institute letter calling for a six-month pause on training frontier models. Three founders who otherwise disagree about almost everything all telling the same story about the existential risk of their own products. Why.

I have........

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