# Geoffrey Hinton said in 2016 that people should stop training radiologists now, that within five years deep learning would do better, and added that it might be ten

Page: https://flyvolo.ai/en/changes/ev-20161124-radiologist-4
Date: 2016-11-24 · Stage: Forecast
Can this record move a task judgement? no
Occupation: https://flyvolo.ai/en/careers/radiologist

## Scope

The recording of the remark itself, published by the conference organiser, 84 seconds long. Read what he actually said rather than the version that circulates, because they differ in a way that matters: the widely repeated form is five years, and the recording continues with a concession the retellings drop — it might be ten years, but we got plenty of radiologists already. He also framed the claim as a prediction about capability, that deep learning would do better than radiologists because it could accumulate more experience, not as a claim about hospitals, employment or regulation. Two limits on this record itself. The words here were read from the video's auto-generated captions, which are a machine transcription, checked against the audio for the sentences quoted but not professionally transcribed. And a forecast is never evidence about work: this record moves nothing on this page, and sits next to the records of what happened — a regulator's authorisation count and a decade of training-post numbers — which is where a reader can do the arithmetic themselves.

## Source

- Creative Destruction Lab — Geoff Hinton: On Radiology, recorded at the 2016 Machine Learning and Market for Intelligence Conference, Toronto — https://www.youtube.com/watch?v=2HMPRXstSvQ (primary source)

## What this means

The most famous prediction about AI and a specific occupation has a recording, a date and a horizon, and all three are now checkable. He said stop training radiologists, gave five years, and — in the sentence the retellings drop — allowed that it might be ten. Both dates have passed or pass this year, and the other records on this page are what happened in between.

## What it does not show yet

It establishes what he said, and nothing about radiology. A forecast is not evidence about work, which is why this record moves no judgement on this page. It also does not establish that he was wrong in the way he is now usually said to have been: his claim was about capability — that deep learning would read better because it could see more cases — not about how many radiologists hospitals would employ, and those two can come apart. What the recording does settle is the wording, which most of the argument about this prediction has been conducted without.

## How to verify it yourself

Watch the eighty-four seconds yourself, then compare them with any article you have read about this prediction. Count how many mention the ten-year fallback. That count is a fact about how claims travel, and it is worth more than one more opinion about radiology.


More: https://flyvolo.ai/llms.txt