Shaping Ethical AI (English version)

What if artificial intelligence were slowly drifting away from reality by feeding on… itself? That is the troubling paradox of data autophagy: when AI models reuse their own outputs, a vicious circle sets in.

🔄 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

For decades, the dominant model of the internet has been the attention economy: capture our gaze, maximise our screen time, turn every second into advertising revenue. But a profound shift is under way. Artificial intelligence no longer merely seeks to capture our attention; it anticipates and shapes our intentions.

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

We swing between fascination and mistrust when it comes to AI. On one side, the enthusiasts who see it as an inevitable revolution. On the other, the sceptics who remind us that “AI won’t bake the baguette”.

But have we asked the right question?

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

Artificial intelligence is transforming our jobs at unprecedented speed. According to the OECD, 32% of today’s jobs will be profoundly changed and 14% completely redesigned by 2030. Faced with this shift, one central question arises: how do we steer this transition rather than simply endure it?

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 in healthcare: revolution or ethical challenge?

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

A third of French people live in medical deserts. A manual worker’s life expectancy is still seven years shorter than a manager’s. Our healthcare system, once a model, is running out of steam. But what if AI and Big Data could change the game?

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

Imagine every piece of music as a unique constellation of stars… and every interaction as an observation that reveals your preferences.

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

AI is no longer just a technology. It is becoming a mirror of our emotions, our consciousness, our relationship with authenticity.

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