I believe one problem is, that computers right now are terrible at considering things up to some equivalence relation. Probably mainly because most equivalence relations are hard to express as computations:
For example it is "easy" for a human to "see" that a coffee cup and a donut are topologically the same, whereas the same task for a computer, i.e. provide it with enough data to recognize something to have exactly one "hole" seems extremely hard. Another example would be to recognize that up to rotation two things are roughly the same. Clearly humans do not solve such problems case by case, they have some build in classifier system that solves those problems by a general principle.
For example it is "easy" for a human to "see" that a coffee cup and a donut are topologically the same, whereas the same task for a computer, i.e. provide it with enough data to recognize something to have exactly one "hole" seems extremely hard. Another example would be to recognize that up to rotation two things are roughly the same. Clearly humans do not solve such problems case by case, they have some build in classifier system that solves those problems by a general principle.