Bob Wachter

So AI was very exciting, but the AI of the day was not ready for prime time for a few reasons.

First of all, it was the old if-then AI.

If a patient has a sore throat and swollen lymph nodes and a fever, they probably have strep throat or mononucleosis.

That works fine for very simple problems, falls apart very quickly, faced with the complexity of real medicine.

The second was all of our data was on paper.

Therefore, if you wanted to use these fancy new AI machines, you had to go to a separate computer and type everything in.

So both of those caused the field to flame out, and AI went away from medicine for about 40 years.

Was this imaging as well or no?

It was early for imaging.

Imaging started in the 80s and 90s.

It was largely around the cognitive work of doctors.

Part of the problem was they started on the hardest problem, and the hardest problem is diagnosis.

I remember speaking to one of the early leaders at the time who was a professor at Stanford.

These are not dummies.

These are MDs and PhDs in computer science.

He said, why did you focus on diagnosis as the first thing to tackle?

He said, we weren't naive about the complexity.

It was just the most interesting problem.

You could understand that.

These were innovators.