I do have my doubts that plain neural networks will ever be able to achieve conceptual understanding. I have an affinity for classical, rational AI in that you can correct it and it will take that correction and instantly apply it to is knowledge base. It can also explain why it came to a conclusion. (though obviously this style has its very real limitations) NNs and other current statistical/connectionist approaches…
I'm a firm believer that it's a mistake to ask machines to do X in the hope that they'll do Y. We can't train an ANN to classify images then ask it to explain its reasoning; that's not the task we trained it for! How might we train an ANN to explain its reasoning? One approach would be to learn programs: have the ANN write programs which classify images. Then we have a classifier (run the program) and an explanation…
It follows that it should be perfectly possible for an A.I. to do this, too.
(Edit: I now realize that this rationalization process was theorized by Douglas Adams in Dirk Gently’s Holistic Detective Agency, as described by Wikipedia:
“The story also mocks the corporate world with [the software] package called Reason, which inverts the idea of a decision-making program. Instead of proceeding from ideas and logic to a decision, it takes a decision that has already been made and creates a reasoned justification for it.”
— https://en.wikipedia.org/wiki/Dirk_Gently%27s_Holistic_Detec... )