Shaping Ethical AI (English version)

Part 2 of 5: Inside the machine.

ChatGPT does not think. And that is even more fascinating than you imagine.

Do you think you are talking to an intelligence? In reality, you are chatting with the most sophisticated parrot ever created.

A parrot that has read the whole of Wikipedia, every book in the French National Library, millions of articles and forums. A parrot able to guess, with unsettling accuracy, the exact word that should come next in any conversation.

Not because it understands. But because it has absorbed the patterns of everything humanity has written.

The difference between thinking and predicting? It is dizzying.

Dive into the heart of the machine. Discover what really lies behind the apparent magic.

Find the full transcript of this episode, along with all the sources and plenty more, at: How ChatGPT revolutionized the world (2/5)

Part 1 of 5: The day everything changed.

November 2022. One button. Five days. One million users.

ChatGPT has just been born, and nobody yet knows that the world will never be quite the same again. What took Facebook 10 months and Netflix three and a half years happened in less than a week.

Today, you talk to it the way you would ask someone the time. 400 million people do so every week. The machine has entered our thoughts. Discreetly. Massively.

But here is the most unsettling part: this revolution rests on a discovery only eight years old. An innocuous-looking paper. An almost bureaucratic title: “Attention Is All You Need”.

Its authors probably did not know they had just rewritten history.

How did a technology colonise our lives so quickly? How can a machine write like Hemingway, code like a senior developer, and sometimes… understand us better than we understand ourselves?

In this five-part series, I invite you on a journey to the heart of this silent revolution. No jargon. No mystification. Just clarity.

Because understanding AI is no longer a luxury. It has become a civic necessity.

Find the full transcript of this episode, along with all the sources and plenty more, at: How ChatGPT revolutionized the world (Part 1/5)

For years, the AI giants played the same lottery: stack ever more layers, pour in ever more computing power, and hope it holds. Sometimes, after months of training and millions of dollars spent, everything collapsed at once. Without warning.

The problem? Nobody really knew why.

Then DeepSeek dug out an old algorithm from 1967, forgotten in a dusty mathematics paper. Something that had nothing to do with AI in the first place. Just matrices and geometry. And with it, they succeeded where others were failing.

This is not just a technical improvement. It is a complete change of philosophy. Proof that you can do better with less, that intelligence is not just a matter of size, but of architecture.

The story of how a 60-year-old algorithm has just reshuffled the cards in the AI race.

Find the full transcript of this episode, along with all the sources and plenty more, at: How a 1960s algorithm just saved AI from chaos

An orchestra without a conductor is organised chaos. Every musician plays in tune, but together, it drifts. AIs are the same. They produce astonishing texts while being capable of going off the rails in any sentence, in the same confident tone. For a long time, we thought there were only two options: talk to them better (prompt engineering) or reprogram them (fine-tuning). But there is a third way, a subtler one. A way of whispering directly into their internal states, while they think.

It is called steering.

Find the full transcript of this episode, along with all the sources and plenty more, at: The art of whispering to AI

Have you ever spent twenty minutes scrolling, reading, watching… then closed LinkedIn with a strange feeling, that of having consumed a lot without really learning anything?

It is not a lack of curiosity or discipline. It is the effect of a new information environment in which AI produces content that is smooth, reassuring, instantly consumable, but often short on substance. It is called AI Slop: intellectual food that fills you up in the moment without ever nourishing thought.

Find the full transcript of this episode, along with all the sources and plenty more, at: AI slop, or the industrial force-feeding of the mind

We spend our time hunting down error, as if it were the enemy of progress. Yet without it, no knowledge would ever emerge, no learning would stand up. Error is the quiet engine of all intelligence.

The trouble starts when we confuse it with deception, and when we project onto our machines the fantasy of a perfection we have never managed to reach ourselves.

Without awareness of our biases, artificial intelligence can only become a magnifying mirror of our own blind spots. This article takes a step to the side, not to condemn technology, but to recall something simple and demanding: it is not the machine that must become perfect, it is our view of our own limits that must become clearer.

Find the full transcript of this episode, along with all the sources and plenty more, at: In praise of imperfection

There is a strange moment when you realise something has tipped over. You log in, you scroll, you click… and you feel a dull wear and tear, as if every gesture took a little more energy than yesterday. The services you loved become heavy, chatty, saturated with prompts. You catch yourself sighing at a news feed that looks less and less like a conversation and more and more like a supermarket concourse on amphetamines.

This shift is no anecdote. It is a precise, patient, almost geometric mechanism. First the platforms seduce us, then they squeeze us, and finally they wring us dry. And we stay put, convinced this is normal. Because “everyone is on it”. Because leaving would cost too much: too much data, too many connections, too many habits.

What if this slow deterioration were not fate, but a system?

What if our tools, designed to make life simpler, had become machines that erode our attention, our knowledge and sometimes even our institutions?

We may have entered an age in which technology no longer merely malfunctions: it methodically decays, and takes us with it. The challenge is no longer to be outraged, but to understand. Because a mechanism, once decoded, stops being a trap.

Find the full transcript of this episode, along with all the sources and plenty more, at: The age of enshittification

Your GPS corrects you before you go wrong. The spellchecker polishes your sentences. The coding assistant guesses your intentions. Everything becomes easier, faster, smoother. But in this slide towards total comfort, something invisible is happening: little by little, we stop thinking for ourselves.

The philosopher Bernard Stiegler had a word for it: the proletarianisation of knowledge. Where the worker once lost his skill to the machine, we are now losing our ability to reflect, decide and create. First, factories dispossessed the hand. Then the culture industries standardised our ways of life. Now artificial intelligence is proletarianising thought itself.

This did not happen overnight. It unfolded in three waves:

The hand: the craftsman becomes a proletarian, the gesture is emptied of its intelligence

Life: the consumer absorbs symbols he no longer creates

Thought: the designer delegates his judgement to the machine

Today, with generative AI, we are crossing a new threshold. Thinking becomes a paid service. Creativity, a premium option. And surveillance capitalism, which already captures our data and predicts our behaviour, is getting ready to monetise even our ideas.

But nothing is inevitable. Stiegler preached neither the rejection of technology nor nostalgia for the past. He invited us to understand that technology is a pharmakon: both poison and cure. It all depends on how we inhabit it.

So what can we do? Take back control of our attention. Steer our tools towards contribution rather than consumption. Make technology an extension of human intelligence, not its substitute. The choice does not belong to the machines. It depends on the care we take of our own thinking.

This is Prometheus’s fire: no longer the stolen flame, but the light preserved.

Find the full transcript of this episode, along with all the sources and plenty more, at: Think as a Service or the proletarianization of knowledge

A few years ago, we complained about having too much information. Today, our brain still runs at its natural pace… but the world has hit x20.

So we wanted to go faster. And we did. So fast that we no longer read, we scroll. So fast that we no longer think, we react. And when we no longer have time to understand, we ask a machine to summarise the world for us. We have handed algorithms the most human things we did: doubting, searching, fumbling, thinking. They answer faster, more clearly, more confidently than we do.

And yet something goes out in that surface perfection: the effort of understanding, the joy of finding, the slowness of meaning taking shape.

In this accelerated world, speed has become an ideal, almost a moral code. But by going fast, we end up going nowhere: we react instead of reflecting, we produce instead of thinking. What if real intelligence were not computing power, but the ability to slow down?

That is what this article is about: the speed that shapes our minds, the trap of automatic thinking, and the clear-eyed slowness we must learn again, not to turn back the clock, but to rediscover the pleasure of inhabiting the world with attention.

Because in the age of artificial intelligence, thinking slowly is no longer a luxury. It is a form of courage.

Find the full transcript of this episode, along with all the sources and plenty more, at: Thinking slowly in an accelerated world

What if, by handing our efforts over to the machine, we were unlearning how to think?

Once upon a time, you had to get lost to learn how to find your way. Today, a synthetic voice guides us step by step, and our mind gently dozes off. We delegate everything: memory to the cloud, logic to the algorithm, decisions to the recommendation. It is comfortable, smooth, almost magical. But that comfort has a price: the slow atrophy of intellectual effort.

We call it progress. Yet behind this promise of efficiency lies a silent drift: cognitive laziness. The imperceptible slide by which we stop reasoning, doubting, searching, and simply approve whatever a machine suggests.

This article explores that phenomenon, not to put technology on trial, but to question what it is making of us: beings ever more assisted, sometimes brilliant on the surface, but less and less present in their own thinking.

What if, in the age of all-round assistance, thinking became our last act of freedom?

Find the full transcript of this episode, along with all the sources and plenty more, at: Cognitive laziness in the age of universal assistance