AI, or artificial intelligence, is huge right now. “Unsolvable” problems are being solved, billions of dollars are being invested, and Microsoft even hired …

There’s an old joke in computer science that goes like this: what’s the difference between AI and automation? Well, automation is what we can do with computers, and AI is what we wish we could do. As soon as we figure out how to do something, it stops being AI and starts being automation.

That joke exists because, even today, AI isn’t well defined—artificial intelligence simply isn’t a technical term. If you were to look it up on Wikipedia, AI is “intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals.” That’s about as vague as you can get.

Generally, there are two kinds of AI: strong AI and weak AI. Strong AI is what most people might be thinking of when they hear AI—some god-like omniscient intelligence like Skynet or Hal 9000 that’s capable of general reasoning and human-like intelligence while surpassing human capabilities.

Weak AIs are highly specialized algorithms designed to answer specific, useful questions in narrowly defined problem domains. A really good chess-playing program, for example, fits this category. The same goes for software that’s really accurate in adjusting insurance premiums. These AI setups are impressive in their own way but very limited overall.  Read more: