A Machine That Dances in Your Place

Sat, 10 Oct 2026 00:00:00 +0000

I am trying to slow down. Not to do less, but to do things properly and give them the time they need. To keep my curiosity, this need I have to understand how things work. To keep my own judgement. It sounds simple. It isn’t, because everything around us pushes the other way, and generative AI pushes hardest. So this post is about that pressure, about what it does to the next generations, and about the one thing it cannot replace: the pleasure of doing difficult work yourself, in your own way. The work some people now call boring.

Slowing down is hard in the times we live in. Generative AI is everywhere and it pushes us to produce more, faster, at the expense of quality and, worse, of judgement. The tools are impressive, I won’t pretend otherwise. The pace they impose is not. It compresses the time we used to need to get somewhere, to reach a result, to find a proof. And that time was not wasted. It was where the understanding happened.

The pressure is real. Social pressure. It comes from work, and it comes from the communities we belong to. If you don’t produce constantly, don’t answer within the hour, don’t have an opinion on every new thing the same day, you are falling behind. But look at what we are in this story. Users. Customers. We don’t build anything. Things get built in front of us and we are invited to watch, and to pay. OpenAI, Anthropic and the others have found a way to sell reasoning by the piece. Tokens, the small fragments of text the machine bills you for, are the new currency. You have to admit it is brilliant. Capitalism has found a way to charge for thought itself. I am not saying everyone who uses these tools has stopped thinking. I am saying the whole business depends on us handing over as much of our thinking as possible, and that this is what the product is designed to encourage.

And what exactly are we handing over? Words. Thoughts. Reasoning. It is easy to forget, with all the talk about intelligence, that these machines produce words, nothing else. With words we write books. With words we think, and I am not sure we can think a thought we have no words for (I started to think about that when I was 17 thanks to my teacher). With words, or with symbols, which are words with a stricter grammar, we prove theorems. The proof of a theorem is not the theorem. It is a text, written by someone, for someone else to read and be convinced. Denis Guedj understood that when he wrote Le Théorème du Perroquet. A mathematician claims to have proved Fermat and Goldbach, refuses to write the proofs down, and recites them to his parrot instead.¹ The parrot can say every word. It understands none of them, and when it loses its memory, the proofs are gone. I read that book a long time ago (around 2015) and I did not expect it to become a description of the present. We are building very large parrots, and we are handing them our words.

What worries me most is the next generations. I think critical thinking is in real danger. I am an involved father, I watch what happens with my own kids and with the children of friends and family, and it is not reassuring. “If ChatGPT can give me the answer, why should I learn?” I have heard this sentence more than once. And yes, ChatGPT will understand a badly written question and come back with an impressive answer. That’s the whole problem.

I am convinced generative AI should simply be banned from schools. And please don’t tell me children need to learn to “master” this technology. That is nonsense. There is nothing to master in typing a question into a box. Anyone who can read, write and think will pick it up in an afternoon, later, when there is something worth asking. Most people just use it, the way they use a search engine or a microwave, except this particular appliance is built at a tremendous cost to the environment. What you cannot pick up in an afternoon is the ability to think for yourself. And that is what gets skipped when the answer is always one question away.

I would go further and keep it out of universities too. This is not only a father talking. In September, twenty-five Fields medalists, Terence Tao and Cédric Villani among them, signed a declaration warning that “the goals of the AI companies and the goals of the mathematical community are severely misaligned”.² Their worry is about pace. A discipline built on slow, careful, verifiable work is being pushed into a race for headlines, and they fear it will break the transmission of knowledge from one generation of mathematicians to the next. If the best mathematicians alive are worried about that, anyone in charge of a classroom should be too.

A month later it got worse. On 6 October OpenAI put online more than 700 manuscripts claiming to settle open mathematical problems. Hugo Duminil-Copin, Fields medal 2022 and one of the initiators of the declaration, told his colleagues at the Société mathématique de France that sixteen of those problems were his, and that he had cried in the night. “They annihilated my research field.”³ What struck me in his talk is not the shock, it is what he said next. He has no desire to read these proofs, because reading them “does not have the same flavour as if they had been written by humans whose faces I know”. He cried for himself, for his colleagues, but mostly for the young, who “will suffer the most”. And he fears for the free circulation of ideas, that culture where you grow by talking openly with your elders and they hand you problems without a second thought. The machines fed on that openness. Now some mathematicians say they will stop sharing what they are working on. That is the transmission of knowledge breaking, in real time, in the one discipline that was supposed to be pure thought.

The numbers are not good either. In France, a 2024 study by the Centre national du livre and Ipsos on 7 to 19 year olds found that young people spend 3 hours and 11 minutes a day on screens and 19 minutes reading books for pleasure. One in five young readers cannot read for more than 15 minutes without stopping. 27 percent of non-readers say they have trouble concentrating, 10 points more than two years before.⁴ That was before generative AI. With it, I think we are heading straight into a wall. Not because people are lazy. Because the easy option always wins when the reward for the hard one is invisible, or comes years later. Nobody sees the understanding you built by struggling with a problem for three hours. Everybody sees the answer.

It is hard to resist the pace when what I really want is to teach the next generations to keep their critical thinking, to enjoy taking their time, to work, and to value work by the time they put into it. I can’t honestly ask my children to do that if I spend my own days racing.

If there is one good thing in all this, it is that it shows what really drives people, in science, in the arts, in the volunteer communities I am part of. There are those who care about the work itself, and those for whom the work is only a means to an end, something to get through rather than something to enjoy. By work I mean making something with your own hands and your own head.

The French literary season gave a good example this year. In September, the debut novel of a much-praised newcomer was accused on social media, on the basis of an AI detector, of having been largely written by a machine.⁵ The accusations are disputed, and anyway that is not the interesting part. The interesting part is how Amélie Nothomb reacted. A few days before the affair broke, she had said that handing your book to an AI proves you are not an author, and compared it to “a machine that would dance in your place”.⁶ Asked later whether the newcomer’s possible use of AI shocked her, she said no, but that she herself could not bear to be helped by anyone, because “difficulty is my pleasure”.⁷ That sentence says it all. The pleasure is in the effort, and the value of the work is the time you put into it. Take that away and what is left is the recognition. Not much.

I also saw her in an interview on French public television. Writing a book, she said, is “épouvantable”, dreadful. And she would never give it to a machine, because this dreadful part is exactly what she loves. The writing itself.

Here is what ties this to the companies. The more work you hand over to the machine, the more money they make. The more work you hand over, the less you learn. These two curves go in opposite directions, and only one of them is on their dashboard. So look at who is pushing us to use generative AI and ask what they want. They built their products on an enormous amount of books, articles and images they never asked for. Now they want us to pay, and they want regulation that locks the technology in their hands. None of them is helping young people focus, learn or read. When did an app last remind you to finish the book you started? You do get a notification when the machine has finished answering, or when a new version is out. Instagram has never once suggested you put the phone down and open a book. Just think about that.

This is not nostalgia and I am not tired of technology. I spend my days with it. I am slowing down because I want to stay someone who can reason, write and learn without asking a machine first, and because the only way I know to pass that on to my kids is to do it in front of them.

Denis Guedj, Le Théorème du Perroquet, Seuil, 1998. English translation: The Parrot’s Theorem, 2000. ↩︎
“25 Fields medalists warn: ‘The goals of the AI companies and the goals of the mathematical community are severely misaligned’”, Le Monde, 11 September 2026. ↩︎
“Nouveau coup de massue d’OpenAI sur les mathématiciens : « Ils ont annihilé mon domaine de recherche »”, Le Monde, 10 October 2026 (subscribers only). Quotes in the original: “Ils ont annihilé mon domaine de recherche”, “Je n’ai pas très envie de lire ces preuves, car le faire n’a pas la même saveur que si cela avait été écrit par des humains dont je connais les visages”, “Ils vont le plus souffrir”, “toute cette culture de la circulation vole en éclats”. ↩︎
Centre national du livre / Ipsos, Les jeunes Français et la lecture, press release of 9 April 2024. Full report: Ipsos. ↩︎
“Affaire Thélyson Orélien : entre rejet viscéral, gêne et fatalisme, le malaise des écrivains français face à l’IA”, franceinfo, October 2026. The novel is C’était ça ou mourir (Grasset); the accusation came from an anonymous X account claiming to have run passages through the Pangram detector. ↩︎
Amélie Nothomb, interview by Aymeric Goetschy for Brut, 12 September 2026: “le confier à l’intelligence artificielle, c’est vraiment avoir prouvé qu’on n’est vraiment pas un auteur” and “c’est exactement comme s’il existait une machine qui allait danser à votre place”. ↩︎
Amélie Nothomb in L’Express, 4 October 2026: “Qu’il ait pu recourir à l’IA ne me choque pas une seconde”, “je ne supporterais pas d’être aidée par qui que ce soit”, “la difficulté, c’est mon plaisir”. ↩︎

Cédric's website

A Machine That Dances in Your Place