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If you want to understand how artificial intelligence will really impact the world, don’t look at coding, law, or finance. Look at healthcare. It is where AI faces its hardest test: layers of regulation, life-or-death stakes, complex biology, and a deeply human, compassionate core that most people would assume is the last thing a machine could replicate.
Nearly a decade ago, computer scientist and Nobel Prize-winner Geoffrey Hinton (known as the “Godfather of AI”) said hospitals should stop training radiologists because, within five years, AI would do the job better. Almost 10 years later, there are more radiologists than ever. Of the 950 artificial intelligence and machine learning tools that received FDA approval between 1995 and 2024, 723 were radiology devices. The machines improved. The humans didn’t leave.
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When I raised this with Hinton recently, he was quick to reframe rather than retreat. What he misjudged, he said, wasn’t the technology. It was the economics.
“Healthcare is a very elastic market,” he told me. “If you allowed a healthcare worker to do ten times as much, we’d just all get ten times as much healthcare. Particularly old people, they can absorb endless amounts of it.”
The standard question—“Will AI replace doctors?”—turns out to be the wrong one. Demand for healthcare is effectively infinite. There is always another scan to read, another condition going undiagnosed because no one has time to look. AI will not shrink the medical workforce. It will expose how much unmet need was always there.
When AI outperforms doctors, and when it fails
In some settings, AI is already surpassing doctors. Cardiologist and researcher Eric Topol pointed to five studies in which AI systems working independently outperformed physicians who had access to AI as a tool. “I still think the combination is likely to win out,” Topol told me. “But I’m not as confident as I was in 2019.”
Why would AI alone…
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