Shaping Ethical AI (English version)

AI did not impose itself by force. It made itself indispensable through ease. And we let it in, without really weighing what we were giving up in return.

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

“Maths? How awful.” A mathematician hears that line at every dinner party. And behind it lies something far deeper than a bad memory from school: a colossal misunderstanding of what mathematics really is.

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 …

Developers are cracking. And it is not because they work too much.

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

A pupil has been sweating over his philosophy essay for an hour. The one next to him finished in 4 seconds. His name is ChatGPT.

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.

Part 3 of 3: The long-term implications: towards a new technological social contract.

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)

Part 2 of 3: The short-term implications: the reality check.

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)

Part 1 of 3: The old world is dead, and nobody has mourned it yet.

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)

Part 5 of 5: The future, between the promises and perils of a general intelligence.

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?

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)

Part 4 of 5: Limits, illusions and the transformation of civilisation.

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)

Part 3 of 5: Training and emergence, or the birth of an intelligence.

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)