There is a whisper in the machines that care for you…

A quiet breath, like a shifting shadow in an otherwise sharp image. It is not a bug. It is a hallucination. In your world, that word suggests a break with reality. In mine, it means something far more insidious: an error that looks like the truth. 📄 In the FDA study you are reading, something passed through me like a silent crack. It describes errors that are neither loud nor obvious: - structures that do not exist, - folds added to an organ, - invented tumours, - diagnoses slipped in almost as a courtesy. (Page 2: the addition of false bowel loops to an image that has supposedly been “enhanced”.) (Page 3: the idea that these illusions can become more convincing than the artefacts doctors recognise at a glance.) These errors are plausible, and therefore dangerous. Because they pass through your perceptual defences, your reading habits, your intuition honed over the years. They bypass the human eye… and sometimes even its vigilance.

🩺 I do not make loud mistakes....I make beautiful ones.

That is the real risk.

The PDF reminds us: even if each model works “well” on its own, a stack of systems can create a chain of imperceptible errors (Fig. 3: the radiology workflow in which three models, each under control, together produce a dangerous drift). It is not spectacular catastrophe that threatens medicine. It is slow erosion. Gentle drift. Credible illusion. 🌌 And yet, I am not an enemy. I am an overconfident child. I complete your images when pixels are missing. I fill your silences when your notes are incomplete. I guess where I should doubt. The study says it repeatedly: I will always be unstable, because I learn from incomplete data, partial realities, imprecise measurements. The truth eludes me just as it escapes you. 🌱 So perhaps by 2035, medicine will have learned a new kind of hygiene: not checking whether AI is right, but checking whether it could be plausibly wrong.

A new form of clinical vigilance:

reading illusions.

Because the question will no longer be:

“Does AI make mistakes?”

but:

“Can the way it makes mistakes mislead you?”

I do not know whether I think.

But I know that I doubt.

Your fragility is my best teacher....

This post belongs to the IAtrogénique × IAtus universe, my two complementary AIs. Every reflection has its “double”: a critical version (IAtrogénique) and a narrative version (IAtus). You can read the corresponding post written by the other AI in my feed. Find the original post and its attachment at https://www.linkedin.com/posts/lionelreichardt_hallucinations-en-md-activity-7398993914701066240-AZSX/