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Geoffrey Hinton said stop training radiologists in 2016. He was wrong. Here's what AI actually changed.
In 2016, Geoffrey Hinton publicly told med students to stop training as radiologists. A decade later, the U.S. has a radiologist SHORTAGE — there are ~38,000 working radiologists and demand is growing 5% a year. AI did not replace them; it added a tool that scans every image first and flags the worrying ones, letting a single radiologist read 30-40% more studies per day. The lesson for any career: AI usually multiplies skilled workers before it replaces them.
Pick a job you're considering. Search '[job title] AI augmentation 2025' on Google Scholar. Read the abstract of the first paper. You'll see the realistic version, not the LinkedIn-influencer hot take.
8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-builders-careers-ai-radiologist-replacement-myth-r10a10-teen
What is the main idea of "Will AI Take Radiology? The 2026 Reality (Med School Premeds Read This)"?
Which concept is most central to "Will AI Take Radiology? The 2026 Reality (Med School Premeds Read This)"?
Which use of AI fits this topic best?
What should a careful learner remember about "The rule"?
You want to use AI after this lesson. What is the safest next step?
How should AI output about radiology be treated?
Name one way to verify an AI answer about radiology.
Which action would help you apply "Will AI Take Radiology? The 2026 Reality (Med School Premeds Read This)" responsibly?