One of the lessons of early AI work was that there's not a lot of overlap between what humans naturally do well and what computers naturally do well. I say "naturally" because much of the work in the ensuing decades has been in enabling machines to do things that don't map naturally to their capabilities.
For example, it's not hard to program a computer to calculate a million decimal digits of pi. It takes some cleverness to produce, say, a billion digits reasonably quickly, but the basic problem is not that hard. On the other hand, it's quite hard to get a machine to recognize faces or walk without tripping over, things which are easy for us.
One crucial aspect of engineering is making the best use of the resources you have. If your resource is a computer, try to put it on problems that involve crunching large amounts of data, not, say, perception, judgment, natural language processing or recognizing objects in the natural world. Machines can deal with those problems, too, to various degrees, but not nearly as easily as we can.
I've called this theme dumb is smarter. Division of labor is complementary. It has to do with putting humans in the loop so that the machines only have to do what they're good at.
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