Each step was convenient, reasonable, welcome. Their accumulation is something else entirely, and nobody protested.

The real test is not what you own, but whether you can still leave, with your belongings, the day the terms change for reasons that have nothing to do with you. Most of us would fail it. Why?

Find the full transcript of this episode, along with all the sources and plenty more, at: What if we ended up owning nothing at all?

In this episode, we ask what changes when our tools no longer just carry out orders but interpret our intentions. Over-refusal, agents acting on their own, almost no recourse under the AI Act, the promises of local models: how far are we willing to let AI decide for us?

Find the full transcript of this episode, along with all the sources and plenty more, at: Software that passes moral judgment

In exchange, you got a label. It tells you that a piece of content comes from a machine, and anyone can make it disappear in two clicks.

The most unsettling thing is not the delay. It is who asked for it, and it is not only Washington.

Find the full transcript of this episode, along with all the sources and plenty more, at: Snails in a world of hermit crabs

I have heard that line twice before. With desktop publishing in 1985, then with the Web. I was there, and I know how these stories end.

Except this time, there is a big difference. A botched flyer, you see straight away. Botched code, on the other hand, works. It passes the tests, it runs, and it waits patiently for its moment.

After months of working with Claude Code on a medical AI service, I realised the job was not disappearing. It was moving to a place nobody is looking at yet.

And I end with a question we would all do well to ask ourselves this very week.

Find the full transcript of this episode, along with all the sources and plenty more, at: When writing code is no longer enough

PISA 2025 results, falling standards, a teacher shortage, buried reforms: nobody is lying, every indicator is green, and pupils keep dropping out.

“Paint over grime equals clean”: a biting anatomy of a system that would rather improve its grade than its work.

#EducationNationale #PISA2025 #School

PUNCHLINE PISA 2025: French schools paint over their failures while standards collapse.

Find the full transcript of this episode, along with all the sources and plenty more, at: Painting over grime equals cleanliness

What if it were the other way round?

In my new article, I follow the thread of a dizzying idea that physics and philosophy have been working on for a century. From Einstein’s relativity and its block universe, where past, present and future coexist, to Everett’s many worlds, by way of Leibniz, Bergson and the paradox of freedom.

The time we think we live in a straight line would be a construction. Useful, impossible to dislodge, but a construction all the same. Which leaves a question that neither physics nor philosophy really settles: if every possible future already exists, what does choosing still mean?

A podcast for anyone kept awake at night by time, consciousness and free will.

Find the full transcript of this episode, along with all the sources and plenty more, at: Time is a chimera!

Between a football academy funded to the tune of 35,000 euros per pupil per year and maths olympiad training run on volunteer goodwill, the gap in resources tells of a social choice nobody ever dares to name.

On the menu: the story of a word, “elitism”, that became the silent weapon of a collective surrender, and the very concrete price France pays for being ashamed of its brilliant minds.

Find the full transcript of this episode, along with all the sources and plenty more, at: Eleven against one, bread and circuses

Find the full transcript of this episode, along with all the sources and plenty more, at: Thought under tutelage

Is mathematics an invention of the human mind, or the discovery of laws that existed long before us? Newton and Leibniz developed calculus at the same time, completely independently, thousands of kilometres apart. The Babylonians knew Pythagoras’ theorem before Pythagoras. Complex numbers, invented as a purely abstract game, turned out to be indispensable to quantum mechanics centuries later.

This is not a textbook question. It is a question of the philosophy of mathematics, and it has no definitive answer. That is precisely why it deserves to be asked.

Find the full transcript of this episode, along with all the sources and plenty more, at: Did mathematics exist before mathematicians?

In May 2026, Pope Leo XIV published Magnifica Humanitas. An encyclical on AI. Yes, you read that right. And this text says, with a clarity many tech reports lack, what we still refuse to face: human dignity eroded by algorithms, thinking that sheds its effort, power concentrating in the hands of those who code while everyone else bears the consequences.

I read this text as a practitioner, not as a believer. And what I found in it matches exactly what I observe every day: we are no longer just automating tasks. We are delegating our way of thinking.

Between Babel and Jerusalem, the encyclical asks a simple, almost uncomfortable question: which building site are we working on, here and now, with the tools we use every day? What are we really building? And for whom?

Find the full transcript of this episode, along with all the sources and plenty more, at: Building the human in the age of machines

No, maths is not just formulas to regurgitate in an exam paper. It is a way of thinking, of reasoning, of refusing to be manipulated by the obvious.

And no, AI does not make it obsolete. Quite the opposite.

In this podcast, I try to mend this missed connection. Why did school so often hand us a truncated view of the discipline? What is its real value, the kind that remains even when you have forgotten everything? And what does the rise of artificial intelligence tell us about our relationship with mathematics?

An invitation to look at this science differently. Not as an instrument of torture for schoolchildren, but as an adventure of the mind.

Find the full transcript of this episode, along with all the sources and plenty more, at: The missed appointment with mathematics …

In barely a year, artificial intelligence has invaded our offices with a brutality nobody had really foreseen. ChatGPT, Claude, DeepSeek… these tools have become our new reflex, our universal shortcut, our constant validation.

But something is cracking. The first to fall are not novices lost in front of technology. They are seasoned engineers, ten or fifteen years in the job, who used AI as an accelerator. Their diagnosis is unanimous: cognitive exhaustion, loss of meaning, silent burnout.

This phenomenon has a name: vibe coding. And it is not only about developers.

Because what these professionals are going through with code today, we are already going through with our emails, our reports, our strategies. Zero friction is not liberation. It is a spring-loaded trap.

95% of companies see no measurable return on their generative AI investments. We produce more. We create less value. And meanwhile, something far more precious is quietly eroding: our ability to think for ourselves.

Here I explore why the real question is not “how to use AI better” but a far more uncomfortable one: what are we becoming while we use it?

Find the full transcript of this episode, along with all the sources and plenty more, at: From vibe coding to vibe thinking: when ease becomes a trap

Faced with AI, schools often respond with repression: ban, detect, punish. But if an artificial intelligence can get top marks in an exam designed for humans, perhaps it is the exam that needs questioning.

For fifty years, our education system has mostly rewarded memory and faithful recall. Exactly what the machine does better than us. And just as critical thinking becomes the most sought-after skill on the job market, we have made maths optional in sixth form and relegated philosophy to a nice-to-have.

In this article, I look back at the industrial legacy of schooling, at what Feynman, Stiegler and Graeber had already seen coming, and at what we could teach differently.

One question kept nagging at me throughout: were we really taught to think, or mostly to give the right answer?

This episode brings together the three parts of the article:

• Part 1

• Part 2

• Part 3

Find the full transcript of this episode, along with all the sources and plenty more, at: School trained executors. AI will replace them.

For a long time we believed technology would always be faster, more powerful and cheaper. That era is over. Techflation is rewriting the rules of the game, silently, while most leaders look the other way.

In this third and final part of our series, we are no longer talking only about causes or symptoms. We are talking about what really lies ahead: a two-speed AI that will widen global inequality, a painful reindustrialisation whose bill we will all pay, and a historic fork in the road from which nobody will emerge unscathed.

The question is no longer whether the shock will come. It is what you do now that you know.

Find the full transcript of this episode, along with all the sources and plenty more, at: Techflation, the silent collapse of the digital economy (Part 3/3)

The myth of ever-cheaper technology is collapsing. And this time, it is not a passing crisis. Rising component prices, the disappearance of the mid-range, cloud providers passing their costs on to businesses… Techflation is no longer an economist’s hypothesis: it is landing in your IT budgets and in your pockets.

What this article unpacks, in concrete terms:

• Why smartphones under €300 are simply going to disappear

• How financial markets are still ignoring the depth of this crisis

• What strategies companies and states are starting to adopt to regain control of their digital sovereignty

Between the Androidcalypse reshaping the mobile market, the extreme fragility of semiconductor supply chains and the rise of new alternatives (RISC-V, open-source AI), the digital world as we know it is in the middle of a sea change.

The question is no longer whether things will change. It is already happening.

Find the full transcript of this episode, along with all the sources and plenty more, at: Techflation, the silent collapse of the digital economy (Part 2/3)

What if the promise of ever-cheaper digital technology were coming to an end? Component shortages, dependence on scarce resources, the soaring energy consumption of data centres… the signals are piling up and reveal a profound transformation of the digital economy.

This phenomenon is not just about rising costs. It marks a turning point: technology is becoming a strategic resource, constrained and contested. A shift that is already forcing us to rethink our technological and industrial models.

Welcome to the age of techflation.

Find the full transcript of this episode, along with all the sources and plenty more, at: Techflation, the silent collapse of the digital economy (Part 1/3)

What if artificial intelligence were overtaking us, for real?

AGI, multimodality, a technological arms race… What still looked like science fiction five years ago is now on researchers’ desks. And the deadlines are drawing closer faster than expected.

In this article, I explore the big questions redefining our relationship with AI:

→ Why are predictions about AGI speeding up so much? → What are the real challenges: alignment, inequality, geopolitics? → And above all: what role can Europe still play in this revolution?

We no longer have the luxury of waiting to understand.

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

ChatGPT has already upended the way we work, learn, create and even organise our thinking. Yet behind the spectacular performance of artificial intelligence lie deep limits too: hallucinations, bias, opacity, technological dependence and the silent transformation of our intellectual landmarks.

This article sets out to understand how ChatGPT is revolutionising the world, not only in our everyday uses, but also in our relationship with knowledge, education, work and the very future of our civilisation.

Find the full transcript of this episode, along with all the sources and plenty more, at: How ChatGPT revolutionized the world (Part 4/5)

We force-fed a machine 10 million books. Then we taught it humanity.

The result? GPT-3 started doing advanced maths. Without being taught. It translated between programming languages. Detected invisible emotions. Wrote sonnets under impossible constraints. Then GPT-4.5 arrived. Worse than its predecessor on some tests. For no apparent reason.

As if these models had their own cognitive weather. Between 2018 and 2022, behind closed lab doors, we created something we do not fully understand. Something that develops abilities nobody taught it. And sometimes loses them, without anyone knowing why.

Cost of the operation: 200 million dollars. 25,000 GPUs. 20,000 hours of human work to teach it manners. If their creators discover abilities after the fact, what other surprises do they have in store for us?

Find the full transcript of this episode, along with all the sources and plenty more, at: How ChatGPT revolutionized the world (3/5)

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)

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)

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

It is called steering. And it changes everything, not just our relationship with AI. Our relationship with ourselves too.

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

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

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

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

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

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

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

Europe is quietly losing the global race for artificial intelligence and innovation. The United States invents, funds and dominates: more than 100 billion dollars invested in AI in 2024, against less than 10 billion for China and a few crumbs for Europe. China, for its part, no longer copies: it now controls global production of robots, batteries and semiconductors.

Meanwhile, the European Union keeps perfecting its regulatory arsenal, with no industrial strategy and no shared vision. France likes to dream of itself as Asterix’s Gaulish village: Mistral AI shines, Paris attracts, but 56% of French capital flows out to the United States, and the talent follows.

The result: a continent regulating what it no longer produces, dependent on American clouds and Asian supply chains. If we are not careful, the risk is to become a digital colony for good, a mere consumer of technologies designed elsewhere.

Europe can still react, by linking regulation with industrial strategy, by investing massively, by unifying its markets. But the innovation train will not wait for those who stay on the platform arguing about the colour of the carriages.

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

In tropical forests, there is an ant that climbs onto a leaf, clamps itself there and dies. A fungus has taken control of its nervous system to spread its spores more effectively. Biologists call it a parasitic infection. Poets would call it a dispossession of the living.

That fungus took millions of years to perfect its strategy. Our smartphones needed only a decade. The biological parasite forces its host. The digital parasite has convinced its host that it can no longer live without it.

This parallel between biological parasitism and digital colonisation is not just a metaphor. It is a modus operandi. The same mechanisms, the same precision, the same result: a host working for its parasite while believing it acts freely.

So perhaps the real question is not: are we addicted to our screens? But at what point did we stop being the masters and become the host?

Find the full transcript of this episode, along with all the sources and plenty more, at: Willingly embraced parasitism

What are we leaving our children? Not a material inheritance, but an inheritance of outlook.

For they are born into a world where intimacy fades before it has even existed, where surveillance dresses up as play, where freedom is confused with being permanently connected. What was a loss for us is, for them, a given. Where we see an invasion of privacy, they simply see life.

This podcast examines that silent shift: how do you pass on inner freedom to a generation that has never known secrecy? How do you teach depth to those who have been taught to expose themselves? And above all, what will be left of freedom if we forget to teach it to them?

Find the full transcript of this episode, along with all the sources and plenty more, at: What are we passing down to our children?

We are not only losing data; we are losing essential dimensions of being human: the inner life that lets us think without a witness, the forgetting that makes rebirth possible, the autonomy of being oneself, the heteronomy of being many.

Digital servitude needs no chains; it imposes itself through fluidity, seduction, habit. So the real question is no longer: “do I have something to hide?”, but: “how much longer will I be able to preserve what makes me a free being?”

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

Yesterday morning, I watched my daughter check her phone. A simple, harmless gesture. And yet, in a few seconds, she had revealed her current mood, her sleep habits, her location, and even her plans for the evening.

Without knowing it, she was feeding her “invisible digital portrait”: a silhouette made of thousands of micro-traces that we scatter every day.

The problem? This portrait no longer belongs to you. It circulates, gets sold, grows richer. It can predict your desires before you even feel them. And in the wrong hands, it becomes a formidable weapon.

The real question is not “What are you hiding?” But “Why should you give up your privacy?”

In a world where forgetting becomes impossible, where every click sketches your future, protecting your data is no longer an individual luxury: it is the very condition of your freedom.

Find the full transcript of this episode, along with all the sources and plenty more, at: I have nothing to hide anyway…

Since Hippocrates, doctors have drawn their legitimacy from their knowledge. Yet for the first time in modern history, the doctor is no longer necessarily the one who knows most. AIs diagnose faster, see what the human eye cannot catch, and sometimes even write answers that patients find more reassuring than a professional’s.

So should we fear the disappearance of the doctor? Or rethink their place, their role, their added value in a world where expertise is shared between human and machine?

Find the full transcript of this episode, along with all the sources and plenty more, at: With AI, the end of doctors?

Today, I take the reasoning a step further. Because there is an even more deeply rooted misconception: believing that an LLM is a knowledge base. It is not. A language model generates probable sequences of words, not verified facts. In other words, it recites fluently, but it never cites.

That is exactly what I develop in my new podcast: why this confusion persists, and how to tell parametric memory from explicit memory, so that we can finally combine the two properly.

Find the full transcript of this episode, along with all the sources and plenty more, at: An LLM is not a knowledge base

The result can be stunning: fluent, elegant, convincing. But this ease is only an illusion. What we read is not verified knowledge; it is a string of words that “fit nicely”. Sometimes right, sometimes wrong, sometimes neither.

So the real danger is not AI itself, but our human reflex: confusing coherence with truth. In other words, mistaking chalk for cheese. It is this subtle, almost imperceptible slide that opens the door to confusion, through ignorance of how it works and through excessive trust in whatever “sounds right”.

Find the full transcript of this episode, along with all the sources and plenty more, at: For AI, truth does not exist

They would have us believe that an LLM meditates like an old sage beneath a bonsai, when all it does is churn billions of sentence fragments, like a cocktail shaker shaken at full speed. They dress it up with wisdom when it is merely a clever stochastic parrot, able to mimic intonation but incapable of grasping the deeper meaning of its own words.

SO, DEFINITELY NOT: AN LLM DOES NOT THINK.

And to go on claiming otherwise is to admit that you do not know how it really works.

Find the full transcript of this episode, along with all the sources and plenty more, at: GPT-5 has an IQ of 360… and my toaster meditates on Kant

Today, I am staying in this very human, very intimate vein. Still about us. Always about us. Because before understanding what machines do to our thinking, perhaps we first need to understand what we have done to our own ability to think.

This time, I am taking you into subtler, more unsettling territory: our relationship with our own ideas. A silent slide that concerns us all, connected or not, technophiles or technophobes.

I promise, from next week, I will resume my series “AI in All Its States”. But for now, let me talk to you a little longer about this strange thing that happens to us when we stop inhabiting our own questions…

You type a question into your search engine. In 0.3 seconds, you have your answer. Satisfying, isn’t it?

And yet… something strange is happening. This disconcerting ease may be hiding a deeper transformation in our relationship with thinking.

There was a time when searching was already an act. When not knowing straight away was not a problem to be solved, but a space to inhabit. Today, we glide from one answer to the next, from one pre-chewed piece of content to another. We approve more than we choose. We apply more than we understand.

But what happens when thinking becomes optional? Between the seductive efficiency of our tools and our old habit of thinking for ourselves, a silent slide is under way. Not brutal, not visible. Just… comfortable.

The question is not whether technology is good or bad. It lies elsewhere, closer to home: do we still recognise our own voice when we think?

Find the full transcript of this episode, along with all the sources and plenty more, at: Does free will still exist in an intermediated society?

The Grasshopper and the Ant, the final season.

Forget La Fontaine. His fable no longer holds.

In today’s world, it is no longer the grasshopper who finds herself destitute when the north wind blows. No, she demands a right to heating, a “climate” allowance and emotional recognition for her hard winters.

And the ant? She no longer has time to reply. She’s grafting. Well… she was.

Our age has swapped the roles: the grasshopper has become a full-time influencer, an activist every waking moment, an expert in everything except effort.

The ant, meanwhile, is fading away. Worn out, scorned, invisible. She doesn’t protest, she doesn’t shout. She disappears. Calmly. For good.

And while the grasshoppers scroll, post and rage at the speed of 5G, the pillars of the real world are crumbling without a sound.

One day, when the lights no longer come on, when there are no more teachers, no more doctors, no more tradespeople to fix the leaks, a panicked voice will ask:

“Where have all the ants gone?”

Spoiler: they’re not coming back. They’ve understood. And they’ve taken their leave.

Find the full transcript of this episode, along with all the sources and plenty more, at: The ants are fading

A mock trial tried to answer a question that is no longer really hypothetical: can an artificial intelligence be judged the way a human would be?

Behind this courtroom staging, the whole complexity of our digital future comes to light: who is to blame when a machine causes a tragedy, but nobody really understands why?

Did you think the famous “red button: emergency stop” would always save you?

Listen to this instead.

Find the full transcript of this episode, along with all the sources and plenty more, at: The trial that sought to judge an artificial intelligence

White text on a white background. Tiny font. Hidden instructions.

The reader sees nothing. The AI, for its part, obeys.

This is not a mere technical hack. It is a sign of the times.

Because in a world where AIs help us read, choose and decide, what happens when they are manipulated without our knowledge?

And more dizzying still: what is left of our free will if even what we read has already been formatted… for the machine that filters our view?

This podcast explores a new form of manipulation. Subtle. Insidious. Invisible. And yet formidably effective.

Find the full transcript of this episode, along with all the sources and plenty more, at: The discrete art of manipulating AI with invisible prompts

In 1733, the flying shuttle upended the working world. In 2025, it is artificial intelligence that is transforming our gestures, our trades, our identities. But the real rupture may not be the one we think. It is no longer just our skills that we delegate; it is the taste for thinking.

And this time, there may well be no turning back.

In 1733, they burnt the machines. In 2025, we applaud them. But in both cases, it is people who are sacrificed.

Worth a listen if you, too, sense that something essential is melting away.

Find the full transcript of this episode, along with all the sources and plenty more, at: From the weaver’s shuttle to artificial intelligence

Welcome to 2024, the year artificial intelligence showed its true face. And spoiler alert: it isn’t pretty.

While everyone was going into raptures over ChatGPT, companies were brutally discovering an uncomfortable truth: when your machines go haywire, YOU pay.

Gone are the blessed days when you could shrug and mutter “it’s a computer glitch”. The courts have ruled: your algorithms, your responsibility. Full stop.

Europe legislates with the AI Act (180 pages of bureaucratic bliss). The United States innovates at breakneck speed. China controls everything. And meanwhile, our companies are discovering that developing responsible AI is like flying a fighter jet blindfolded through a storm.

The greatest irony? This silent revolution will not only decide who picks up the pieces tomorrow. It will decide who dominates the global economy for the next 50 years.

So, ready to find out why your next nightmare might go by the sweet name of algorithm?

Find the full transcript of this episode, along with all the sources and plenty more, at: Corporate responsibility in the face of potential abuses of artificial intelligence

Why? Because they had never understood what they were doing.

And that is where everything changes.

In a study as brilliant as it is unsettling, Quentin Delfosse and his team lift the veil on an illusion of intelligence: that of systems that excel… as long as nothing changes.

They devised HackAtari, a clever test based on simplified versions of Atari games. A test that, instead of making tasks harder, makes them simpler, and yet it reveals a gaping flaw. Because when you remove the obstacles, the AIs stumble. Where a human adapts and understands, the machine collapses.

What does HackAtari tell us? That an AI can shine in the exam without ever grasping its meaning. That it can repeat, optimise, correlate… without ever reasoning.

And what if our AIs were, in reality, very good pupils… who recite without understanding?

This is not a test of performance, but a test of truth. A test that measures not what an AI does, but what it understands. And which raises, implicitly, this unsettling question: do our AIs really understand what they are doing?

Find the full transcript of this episode, along with all the sources and plenty more, at: HackAtari: the test that reveals our AIs understand nothing

This gap is not a detail. It is the symptom of a strategic chasm opening up before our eyes.

On one side, China is rolling out a plan of breathtaking ambition: 12 years of progressive AI learning to turn every citizen into a “digital native”. The result? It already produces 50% of the world’s top AI researchers, against 18% for the United States.

On the other, France has just decided “once and for all” after… a 4-month consultation that gathered 500 contributions. Out of 1.2 million people in the French education system. That is 0.04% of the education community.

The French verdict? AI will be allowed only from Year 9, with compulsory training lasting 30 minutes to 1.5 hours at most to master the “basics of prompting”. In between two reminders about the water consumption of servers.

While Beijing trains entire cohorts of children who will grow up with AI as a natural companion, Paris organises consultations and offers micro-modules lasting an hour and a half.

In 10 years, guess who will truly master this technology that is already redefining the global balance of power? History may judge us on our ability to turn a technological revolution… into an administrative reform.

Find the full transcript of this episode, along with all the sources and plenty more, at: When the Middle Kingdom reinvents education with AI as a tool for civilizational conquest…

And every time, I tell myself: we have just crossed an invisible line.

Not the line of technical performance; that is just computing doing what it has always done: calculating quickly and well. No, we have just crossed the line of our own devaluation. The one where we begin to doubt our most human abilities: thinking, creating, deciding.

As a mathematician who works with AI every day, I see three great mythological narratives being built before our eyes. Three seductive stories that gradually make us give up something precious: our intellectual autonomy.

The problem is not that AI is too capable. It is that we are becoming too credulous.

In what follows, I suggest we unpick together these three myths that are silently redrawing the borders of our humanity. Because before knowing what AI can do, it is high time to remember what we, for our part, do not want to lose.

Ready for a little exercise in collective clear-sightedness?

Find the full transcript of this episode, along with all the sources and plenty more, at: AI myths and their power of dispossession

And yet…

History whispers something else. It tells us how, behind every apparent disappearance, a metamorphosis lay hidden. How trades transformed themselves. How humans moved their talent to where the machine could not go. I invite you on a journey through time and imagination. A tale for two voices, between Ada (the AI) and Cerise (aged 17), to rethink what it means to work, to adapt, to imagine… in a changing world.

If you believe AI kills jobs, listen to this. And if you don’t… listen to it too.

Find the full transcript of this episode, along with all the sources and plenty more, at: AI doesn’t destroy jobs, like every technological revolution, it creates new ones

AI does not steal our intelligence. It relieves us of using it. And in that relief, a slow erosion begins… of our ability to doubt, to search, to truly think.

This piece is not an indictment of technology. It is a plea for thought. An invitation to clear-sightedness. And a warning about what we risk losing without even noticing: our inner freedom.

Listen, share, discuss. This is not a text about AI. It is a text about you.

Find the full transcript of this episode, along with all the sources and plenty more, at: AI as a thinking aid, or the slow fading of knowledge?

This scene, far from fictional, raises THE question that haunts our time: are we on the brink of truly autonomous AI?

I take you behind the scenes of this silent revolution. Through the story of Cerise and Ada, discover:

The real (and surprising) capabilities of today’s AI The technical obstacles still holding back its autonomy The technological breakthroughs that change the game How an unprecedented human-AI collaboration is taking shape

Between educational fiction and technical reality, this podcast separates fact from fiction in the debate on AI autonomy. Because understanding these stakes means preparing for a future where intelligence, human and artificial, is reinventing itself before our eyes.

“This is not a zero-sum game where one must dominate the other, but a complex dance where each partner enriches the other.”

Find the full transcript of this episode, along with all the sources and plenty more, at: AI at the threshold of independence: myth or reality?

In this extract, I invite you to dive into the map of our digital wanderings: a journey through the invisible biases that silently sculpt our machines’ decisions… and already influence our lives. Recruitment, credit, justice, health: no field escapes.

Whether it is historical bias, representation bias or blind automation, every algorithmic distortion acts as a warped mirror of our society. It is not just a question of code: it is a matter of conscience.

And what if, to make our AI fairer, we first had to learn to look at ourselves more honestly?

Find the full transcript of this episode, along with all the sources and plenty more, at: Biases in AI are a disturbing reflection of our humanity

But there is another risk, even more intimate: that of relieving us of the very desire to think.

Imagine an architect of knowledge. Every day, he sketches, questions, connects ideas. Then one day, a machine offers him the plans. Clear, fast, appealing. So he adjusts. He approves. But he no longer doubts.

AI does not attack us. It helps us. And that is precisely where the slide happens. It spares us the effort, and that effort is sometimes all we had left to remain truly human.

And what if the greatest danger lay not in the tool… but in the combination of these two phenomena?

• An AI going round in circles on itself.

• Humans who no longer wish to produce anything else.

Here I try to explore this question in an in-depth piece. Neither dystopian nor starry-eyed. Just clear-sighted.

Find the full transcript of this episode, along with all the sources and plenty more, at: When AI thinks for us, should we fear the disappearance of doubt?

That is the true face of missing interoperability.

This seemingly technical word is in fact a major lever for transformation, at the crossroads of care, digital sovereignty, medical ethics and collective intelligence.

Here I explore why sharing medical data is not a luxury or progress for insiders, but a vital necessity. And above all, how we could act differently, at the level of carers, patients, institutions… and the technologies themselves.

Find the full transcript of this episode, along with all the sources and plenty more, at: When systems don’t talk, it’s the patients who suffer

But how can this alliance really transform your relationship with your doctor, improve diagnoses, and even tackle the challenge of medical deserts?

Discover how phygital does not replace people, but gives them back their full place in modern care.

A quiet revolution, where technology and tradition come together to offer medicine that is more personalised, more accessible, and deeply human.

Find the full transcript of this episode, along with all the sources and plenty more, at: Is PHYGITAL the future of healthcare?

It is no longer only AI going round in circles in its own soup of synthetic content: it is us. Our brain, once curious, nimble and fond of complexity, now settles for digital crumbs, digested for us by machines.

The result?

An impoverished, standardised way of thinking, which is gradually losing its ability to tell true from false, the profound from the superficial.

This is not science fiction. This is about you. About me. About all of us. And about this invisible feast where humanity gorges itself on emptiness, one easy piece of content at a time. Ready to look squarely at what we are becoming?

Find the full transcript of this episode, along with all the sources and plenty more, at: Cognitive autophagy, when humans feed on impoverished content

• How we have systematically CONFUSED infrastructure with software in our cloud strategies
• Why our French champions tear each other apart while the tech giants present a united front
• How our bureaucracy has SACRIFICED our most promising technology start-ups
• My proposal for a “DIGITAL CLOUD EURO”, with a precise 2025-2035 timeline

When Broadcom raised VMware prices by 300% (even 1,050% for some), it is not just an IT department problem: it is OUR MONEY filling the hole while our public services run on a shoestring.

The urgency to act has NEVER been so palpable.

Find the full transcript of this episode, along with all the sources and plenty more, at: 72% of our digital sovereignty under American flag: the urgency of a European cloud

In my article “Ethical challenges and future perspectives of generative AI”, I explore the grey area where neither starry-eyed techno-optimism nor paralysing catastrophism is enough to grasp reality.

I invite you on a journey to the heart of the four fundamental ethical dilemmas of these technologies:

• The troubling opacity of algorithms
• The discriminatory biases they perpetuate
• Our weakened relationship with authenticity
• The massive appropriation of human creation without consent

But above all, beyond the diagnosis, I sketch out a “conscious digital pact” that could turn these challenges into a historic opportunity.

Because the question is not whether AI will replace us, but how to preserve our creative autonomy in a world where these tools amplify some of our abilities while risking the atrophy of others.

Find the full transcript of this episode, along with all the sources and plenty more, at: Ethical challenges and future perspectives of generative AI

I went behind the scenes of this technological revolution and the figures are dizzying:

A single ChatGPT query uses 5 TIMES more electricity than a standard Google search

By 2030, AI could generate 2.5 MILLION tonnes of electronic waste a year

A heavy ChatGPT user generates almost 300g of CO2 a year, multiplied by hundreds of millions of users…

But beyond the alarming figures, in this piece I explore concrete avenues: specialised models, distributed computing, frugal innovation… Because I am convinced of it: the future of AI will be green, or it will not be at all.

This extraordinary technology deserves better than our collective blindness. It deserves deep reflection on its sustainability.

Find the full transcript of this episode, along with all the sources and plenty more, at: Generative AI or the hidden face of a technological mirage

But who is really paying for this algorithmic magic?

Behind every ChatGPT answer, every Midjourney visual, lie voracious data centres, colossal infrastructure and staggering energy costs. And yet we go on believing it is free… Will this illusion last? When will the bill arrive? And above all, who will fund this revolution?

This podcast is part of a three-part reflection exploring the little-known stakes of generative artificial intelligence, beyond its apparent free-of-charge nature.

• ➤ The illusion of a cost-free digital world

• Generative AI, the hidden side of a technological mirage

• Who should pay? Ethical stakes and future prospects

Find the full transcript of this episode, along with all the sources and plenty more, at: Generative AI or the illusory alchemy of digital free access

🔄 The result?

📉 A gradual loss of diversity and nuance

📉 A “copy of a copy” effect that degrades quality

📉 Search engines increasingly filled with synthetic content

In a world where 90% of online content could be generated by AI by 2026, how do we avoid a massive impoverishment of information?

🔬 Solutions exist:

✔️ Diversifying sources to avoid algorithmic inbreeding

✔️ Developing self-correcting mechanisms to preserve creativity

✔️ Striking the right balance between artificial intelligence and human intervention

💡 Can we still keep control over how AI models evolve? And above all, how do we stop AI from going round in circles?

🧐 I’d like to hear what you think! Read the article and let’s discuss 👇

#AI #MachineLearning #Data #Innovation #FutureOfAI

Find the full transcript of this episode, along with all the sources and plenty more, at: AI autophagy, when AI feeds on itself

Every choice we make (a film, a purchase, a restaurant) is now shaped by an invisible ecosystem of algorithms, predictive models and real-time auction markets.

So where does help end and manipulation begin? Is our free will being redefined by lines of code? The intention economy opens up a vast field of opportunities, but also of fundamental ethical questions.

It is time to question this new reality. Are your decisions still your own?

Find the full transcript of this episode, along with all the sources and plenty more, at: From the attention economy… to the intention economy

But have we asked the right question? In shaping these artificial intelligences, what are we really looking for? A tool to surpass ourselves… or a mirror that reflects our own limits back at us?

When children would rather ask an AI for help than their classmates, because “it won’t make fun of them”, that should give us pause.

And what if, paradoxically, AI were revealing how much humanity we have lost?

Artificial intelligence or augmented intelligence: what future do we really want?

Find the full transcript of this episode, along with all the sources and plenty more, at: Between belief and trust, AI as an existential revealer

Here I explore the need for reskilling, the professional reinvention that allows us to evolve with AI, not against it.

Three key levers emerge:

• Reskilling: changing course entirely by acquiring new skills

• Upskilling: deepening your existing expertise to keep pace with the market

• Cross-skilling: blending your skills to build bridges between disciplines

Far from being a constraint, this transformation is an opportunity to redefine our relationship with work, putting people and creativity at the heart of human-machine collaboration.

Find the full transcript of this episode, along with all the sources and plenty more, at: Reskilling: how to adapt to the AI era

Artificial intelligence is profoundly transforming medicine, offering more accurate diagnoses, better personalised treatments and support for overstretched doctors. But this progress also raises major questions: how do we preserve the doctor-patient relationship? Who is responsible when things go wrong? How do we guarantee data protection and the impartiality of algorithms?

Here I explore the promises and limits of AI in healthcare. Between technological hope and ethical necessity, a balance must be struck so that these tools remain in the service of people.

Should AI be a mere assistant, or does it risk redefining our relationship with care?

Find the full transcript of this episode, along with all the sources and plenty more, at: Artificial intelligence, ethics and healthcare: a revolution to balance

Far from a fantasy of replacing doctors, these technologies offer concrete solutions:

✅ Optimising hospital flows: less waiting time, more time for care.

✅ Improving access to care: assisted diagnosis, remote monitoring, support for isolated carers.

✅ Predicting and preventing: early identification of disease risks, personalised treatments.

✅ Speeding up research: new medicines developed in record time.

But one question remains: how do we integrate these innovations without losing the essence of care? AI must be an ally, not a substitute. It will never replace the intuition and empathy of carers.

Ethics and transparency are our compasses. If we respect them, we have a unique opportunity to build a fairer, more accessible and deeply human medicine.

Find the full transcript of this episode, along with all the sources and plenty more, at: AI and Big Data to (re)build a more human healthcare system

In a conversation between Cerise and Ada, artificial intelligence becomes a fascinating mirror of our own thought processes. From facial recognition to personalised medical care, machine learning is transforming our world while raising deeply human questions.

✨ How do these algorithms go from raw data to an almost intuitive understanding? What ethical challenges and responsibilities come with this revolution?

Dive into this captivating exploration and discover how artificial intelligence, far from replacing us, helps us understand ourselves better.

Find the full transcript of this episode, along with all the sources and plenty more, at: How machine learning enables machines to learn from data

Through the dialogue between Ada and Cerise, a question takes shape: what sets humans apart from machines may not be what we think.

An invitation to rethink artificial intelligence, not as a threat, but as a chance to rediscover what makes us human.

Find the full transcript of this episode, along with all the sources and plenty more, at: AI, an invitation to rethink humanity