Artificial Intelligence Requires More Human Intelligence

Human judgment under probabilistic systems

By: Eduardo Valencia

Narrated by: Virtual Voice

A system that was right on average—and humans who could not accept what that meant.

In 2019, an automated pricing system contracted by Pfizer recommended bids for public pharmaceutical tenders in Denmark. It was not a prototype. It was in production, evaluated every two weeks with real money at stake. The system worked—it outperformed human judgment in aggregate. And still, it was often ignored.

Not because it failed spectacularly. But because it succeeded in a way humans struggle to integrate.

This book describes what happens when machines begin to make better decisions on average—and humans are still responsible for deciding whether to follow them. From pharmaceutical pricing in Denmark to adaptive language learning in the Basque Country to internal AI systems at Reddit, the same pattern emerges: humans correcting individual outcomes in systems designed for aggregate gain. Each override is reasonable. Each is locally defensible. Together, they produce a worse result.

This is not a book against AI. It is not a guide to AI tools. It is not a policy proposal or a philosophical treatise.

It is testimony—written from inside the systems, by someone who watched the failures unfold in real time and had to decide what to do about them.

Eduardo Valencia combines a background in philology, public policy evaluation, and applied econometrics. He has worked on AI-integrated decision systems in pharmaceutical pricing, adaptive learning platforms, and organizational design.