Mass-Delusion

26 July 2026 Generative AI Charlie Warzel Cory Doctorow John Gruber Karen Hao Moore’s Law

Last summer, Charlie Warzel wrote a piece for The Atlantic that’s been bumping around in my head ever since. In “AI is a mass-delusion event”, he not only criticizes the hype about generative AI, but wonders aloud what’ll happen if it never fulfills its champions’ expectations:

Lately, I’ve been preoccupied with a different question: What if generative AI isn’t God in the machine or vaporware? What if it’s just good enough, useful to many without being revolutionary? Right now, the models don’t think—they predict and arrange tokens of language to provide plausible responses to queries. There is little compelling evidence that they will evolve without some kind of quantum research leap. What if they never stop hallucinating and never develop the kind of creative ingenuity that powers actual human intelligence?

Good enough is the never-quite-here-nor-there scenario, the one where the many downsides never add up to any tangible benefit.

[…] What if the real doomer scenario is that we pollute the internet and the planet, reorient our economy and leverage ourselves, outsource big chunks of our minds, realign our geopolitics and culture, and fight endlessly over a technology that never comes close to delivering on its grandest promises? What if we spend so much time waiting and arguing that we fail to marshal our energy toward addressing the problems that exist here and now? […]

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Over the winter, I attended an event about occupational safety¹. What jumped out at me was the palpable sense among people (working for established, mid- to large-sized German companies) that some profound, AI-induced change was on the horizon. AI was being cast as an opportunity for sure, but overwhelmingly as some kind of inevitable force that had to be adopted unless you wanted to be left behind.

I understand that there are many different views on AI, but one thing is certain: Everyone is talking about it, all the time. The cultural shift is profound, the topic occupies a huge part of the public imagination, but that prominence is unmatched (at least in my experience) by any real, positive change.

I’ll hear stories about job loss and uncertainly, fear of missing out, an almost religious believe that “it will get better” and more capable. I hear about the job market becoming a competition between AI-written resumés and AI-powered resumé-scanners, coders having to babysit AI tools instead of writing code themselves. There are some short-term convenience gains, but the overall experience is miserable.

That’s where I disagree with Charlie Warzel: I don’t think the majority of people are delusional themselves. They aren’t having the kind of experience that makes them believe AI is a force for good, but they are noticing the effects the delusion is having on their work lives. To paraphrase Cory Doctorow: A whole lot of people don’t believe in AI, but believe that other people will believe in AI.

John Gruber has a apt take on this:

Per Clarke’s third law, “Any sufficiently advanced technology is indistinguishable from magic”. Generative AI feels a bit magical to all of us, even those of us with mid-to-high levels of understanding how computers work and how to make them work. But it feels like the first time ever that computers have been tools for their own creation for a lot of rather dimwitted but confident corporate manager/executive types. This moment feels like the Big Bang to them. The religiosity of this is such that there is no way to convince them that AI, as it stands today, is impressive and useful and innovative, yes, but several orders of magnitude less so than they’re imagining that it is.

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I haven’t finished Karen Hao’s Empire of AI yet, but what’s already clear from her retelling of technology’s history is how much of where we are has been been a deliberate choice, not an inevitability. Hao likens the development of AI to Moore’s Law. The delusion? Accepting AI as an inevitability.

In the end, Moore’s Law was not based on some principle of physics. It was an economic and political observation that Moore made about the rate of progress that he could drive his company to achieve, and an economic and political choice that he made to follow it. When he did, Moore took the rest of the computer chip industry with him, as other companies realized it was the most competitive business strategy. OpenAI’s Law, or what the company would later replace with an even more fevered pursuit of so-called scaling laws, is exactly the same. It is not a natural phenomenon. It’s a self-fulfilling prophecy.

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