Aside from the scare quotes, you're wrong, "machine teaching" and "expert systems" are not the same thing (and neither is considered the same as pre-deep nets computer vission). In my still-shallow research, machine teaching is a conceptual thread that began years ago but is still active and interacts deep learning currents. Expert systems are still around also, they just aren't considered AI anymore.

See: https://blogs.microsoft.com/ai/machine-teaching/ and so forth.

It's a bit different from expert systems or knowledge bases IMHO. To my limited knowledge in the medical imaging field feature engineering is still very much a trusted tool (experts tuning systems based on their domain knowledge).

https://en.wikipedia.org/wiki/Feature_engineering

I find it interesting that you put scare quotes around AI to speak of the dominant trend of AI research in the last 70 years (not expert systems, but manual coding of proposed intellectual mechanisms).

I am curious. Can you explain why you use scare quotes?

Because all AI is ML, obviously. All that stuff before massive GPU farms? Not real AI. (I'm not sure why this is a common perception.)