2016: @GeoffreyHinton says we should stop training radiologists, because radiologists will soon be replaced by deep learning 2019: There is a shortage of radiologists. # replaced ≈ 0 What did Hinton miss? by @garymarcus & @MaxALittle⁩

An astute critic of deep learning, @GaryMarcus, takes on radiology AI: "The laboratory evidence for the effectiveness of deep learning is not as sound as it might seem... For patient safety, it is important we be leery of premature declarations of victory"

Opinion: The long-promised AI revolution in #healthcare may someday arrive, but for patient safety, it is important we be leery of premature declarations of victory.

@professor_ajay @joshgans @avicgoldfarb @jasonfurman @GaryMarcus @NYUStern Today's @NYUStern #ManagingAI poll: Will AI reduce the need for radiologists? Before reading @GaryMarcus and @MaxALittle: 37.5% Yes After reading: 25% Yes Here's the reading

@AndrewOrlowski @GaryMarcus @MelMitchell1 @filippie509 @StandardDevs Excellent article. Gary and I wrote about the consequences of this for medicine

"In drug trials, it is a given that success in Phase 1 is no guarantee of success in Phase 3... (I)n the current mania for #DeepLearning and #AI, a preliminary proof of concept" suffices "to revamp medical school curricula" writes @GaryMarcus #AIhealthcare

Three years ago, AI pioneer Geoffrey Hinton said “We should stop training radiologists now, deep learning is going to do better than radiologists.” But the number of radiologists replaced by AI is approximately zero, and there is a worldwide shortage. Why?