Clinical intuition and mind wandering may be computationally optimal strategies for complex realities.

Random experimentation produced accurate accounts of reality across all conditions tested.

Random experimentation and unfocused thinking can benefit a person by challenging unconscious scripts.

Some clinicians have an uncanny quality. A colleague describes herself and others with this instinct as "witchy"—a capacity to know things about patients they haven't said yet, to follow a stray association to a song lyric or a half-remembered cultural reference and arrive, reliably, at something the patient urgently needed to say but couldn't reach on their own.

We see with artificial intelligence these intriguing possibilities for discovery, especially as connections that human beings never would see pop out of apparently unrelated data. Despite the risk of hallucination, we also see remarkable progress on the horizon.

AI mirrors this "witchy" instinct. In medicine, key findings have surfaced from apparently unrelated retinal scans (Zhou et al. 2023). RETFound, for example, predicted Parkinson's or heart attacks from eye images meant for glaucoma detection, which humans can't determine from routine exams. With safeguards against errors, AI promises to systematize serendipity, transforming clinical hunches into scalable discoveries for millions.

It is becoming increasingly evident that information surrounds us, and we can draw meaning from it if we know how to look.1

Demystifying Mysticism

A new paper in Collective Intelligence (Dubova, Moskvichev, & Zollman, 2026) may offer the first formal computational explanation for why this kind of knowing works—and why more disciplined, theory-driven approaches often fail in ways invisible to the people using them.

The researchers simulated scientific communities—agents collecting data, building theories, sharing findings—and pitted every major philosophical strategy for choosing experiments........

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