NY Times revisits Nobel Prize winner’s prediction AI will render radiologists obsolete
The New York Times on Wednesday revisited a recent Nobel Prize winner’s prediction that artificial intelligence would render radiologists obsolete.
Nine years ago, scientist Geoffrey Hinton famously said, “People should stop training radiologists now,” believing it was “completely obvious” AI would outperform human rads within five years. Fast forward to today and the prediction has proven far from prescient.
Since 2016, the Mayo Clinic in Rochester, Minnesota, has seen its staff grow by 55%, up to 400 radiologists. The American College of Radiology also released a report earlier this year, the Times noted, forecasting the specialty’s supply of physicians will grow by 26% in the next 30 years.
“Would [AI] replace radiologists? We didn’t think so,” Matthew Callstrom, MD, PhD, Mayo’s chair of radiology, told the Times when recalling the prediction. “We knew how hard it is and all that is involved.”
The article explores ways in which Mayo Clinic radiologists are using AI to simplify their work—sharpening images, automating routine tasks, identifying abnormalities and predicting disease. Callstrom and colleagues, spurred by Hinton’s prediction, formed a team to assess AI options with a goal to “make us better.” Today, the health system is using over 250 AI models concentrated in radiology and cardiology.
“So far, AI is proving to be a powerful medical tool to increase efficiency and magnify human abilities, rather than take anyone’s job,” reporter Steve Lohr writes.
The piece closes by asking Hinton to revisit his prediction. In retrospect, the physicist said he may have spoken too broadly and did not make it clear he was only referring to image analysis. Hinton believes he was wrong about timing but not the direction AI would take the specialty. In the coming years, he expects interpretations to be handled by a combo of physicians and AI, which will “make radiologists a whole lot more efficient in addition to improving accuracy.”
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