I've been informally A/B testing the terms machine learning, artificial intelligence, and computational statistics:

- Machine learning: "Oh, neat, what are you working on?"

- Artificial intelligence: "What do you think about the singularity?" or [rolls eyes]

- Computational statistics: "That's nice. So, how was your weekend?"

I generally agree with this. I used machine learning almost exclusively in the article. Yet "AI misinformation" seems more appropriate in the title since the misinformation, generally, is in reference to "artificial intelligence".

Yup, we've had several AI winters. Now we have an AI Spring of Hype. Then we will have a Summer of Hope. Then a Fall of Failure. Then another, long AI Winter.

Sounds like VR hype through the ages..

Agreed, FI -for fake intelligence- would be more accurate :)

I think AI is accurate, but it's actually short for "aggregated intelligence". Most AI algorithms can't actually generate "intelligence" as we know it. Rather, they aggregate the intelligence of the humans who contributed to their training data, and then generalize it to situations where those humans are not present. If the humans are stupid (as we saw with Microsoft's Tay chatbot), the AI is going to be pretty stupid as well. If the humans are racist, the AI is going to be racist as well.

> Most AI

AlphaGo would be an example. It was trained by self play.

Bootstrapped by supervised learning though: it was trained with the results of 30 million human games before the reinforcement learning kicked in.

Expert systems (which is what you're describing) are generally considered to belong in the AI category.

Not just expert systems: any supervised learning system also fits into this category (including neural nets), as do Markov chains, collaborative filtering, Bayesian inference, anything that involves counting actions that humans take.

Maybe we're "fake intelligences" too. Just a bunch of proteins and water, performing chemical reactions.