[dmos62]

Well that depends on your definition of AI. Which isn't well defined. We call AI what we perceive as "magic". Black box algorithms have a higher chance of being perceived that way (e.g. neural nets). When you get some insight into how an algorithm works (easier for transparent box algos, but same holds for black box algorithms), you start to see it less and less as "magic", and, consequently, you're less likely to refer to it as an (artificial) intelligence. Because ultimately, that's what we mean by intelligence -- magic. When we say that something is intelligent, we liken it to ourselves: it evokes a sense of identification. It all comes back to a sense of humans being fundamentally separate from "the other" (computers in this case). If we saw the mathematical models and algorithms as just that, we wouldn't call them AI. Also, if we didn't think of our intelligence as more than the behaviour of our biological computer, we wouldn't be enchanted by the concept of non-biological systems mimicking some of our behaviour.

[Uberphallus]

A professor once told in class "when it works and you don't understand why, it's called AI; when you do, it's called algorithm"

[mjburgess]

I disagree.

We don't find these systems intelligent because, on inspection, they arent.

We are intelligent. Not "magically", but actually nevertheless.

Our intelligence, and that of dogs (, mice, etc.) consists in the ability to operate on partial models of environments; dynamically responsive to them; and to skilfully respond to changes in them.

This sort of intelligence requires the environment to physically reconstitue the animal in order to non-cognitively develop skills.

It is skillful action we are interested in; and precisely what I missing in naive rule-based models of congition.

[dmos62]

You provided an illustration of "magic". It's important to realise that you don't need a complex algorithm to produce complex behaviour (see Stephen Wolfram and his work on cellular automata).