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On the other hand, we are today daily using tools that 20 years ago certainly was studied as AI, such as speech recognition and image classification. Maybe they

by Ma8ee 6y ago

On the other hand, we are today daily using tools that 20 years ago certainly was studied as AI, such as speech recognition and image classification. Maybe they are not using general artificial intelligence to do it, but I think that is beside the point. They are accomplishing something that used to be thought to require some kind of intelligence to accomplish. But as soon we succeed with one of these tasks, the magic disappears among the practitioners, and the goalpost for what is allowed to be called AI is moved. Our understanding what intelligence really is, is very vague to begin with, so what’s wrong with calling progress in machine learning AI even after we actually succeeded with something?

unishark 6y ago
I agree there is a moving goalpost for what counts as good enough to call "AI". But with the recent revolution in machine learning the goalpost kind of went backwards. The successes in machine learning problems have tended to come from "adjacent" fields like pattern recognition, information retrieval, plain old statistics, etc. Meanwhile the AI researchers were pursuing more ambitious directions that didn't pan out. Then AI researchers basically "annexed" these lower level methods that worked.
wolki 6y ago
There's nothing wrong with it, it can simply lead to confusion. When computers started, people called them 'thinking machines' and, say, multiplication was something that required some intelligent behavior on the part of the person doing it. There's nothing wrong with calling a calculator a thinking machine that implements intelligent behavior, but it helps if everyone is aware that at other times when people talk about 'thinking' and 'intelligent' they mean something quite different. This is not uncommon; when people use the word 'bank' they refer to very different things: river ones, park ones, central ones, rotations of flying objects etc. But everyone should be aware that getting better at building comfortable banks to sit on in the park is not the same as getting better at figuring out the optimal rate of interest or turning planes. It certainly might, but that is a separate argument and terminology can obscure that.

by Ma8ee 6y ago

unishark 6y ago

I agree there is a moving goalpost for what counts as good enough to call "AI". But with the recent revolution in machine learning the goalpost kind of went backwards. The successes in machine learning problems have tended to come from "adjacent" fields like pattern recognition, information retrieval, plain old statistics, etc. Meanwhile the AI researchers were pursuing more ambitious directions that didn't pan out. Then AI researchers basically "annexed" these lower level methods that worked.

wolki 6y ago

There's nothing wrong with it, it can simply lead to confusion. When computers started, people called them 'thinking machines' and, say, multiplication was something that required some intelligent behavior on the part of the person doing it. There's nothing wrong with calling a calculator a thinking machine that implements intelligent behavior, but it helps if everyone is aware that at other times when people talk about 'thinking' and 'intelligent' they mean something quite different. This is not uncommon; when people use the word 'bank' they refer to very different things: river ones, park ones, central ones, rotations of flying objects etc. But everyone should be aware that getting better at building comfortable banks to sit on in the park is not the same as getting better at figuring out the optimal rate of interest or turning planes. It certainly might, but that is a separate argument and terminology can obscure that.