If we genuinely had no idea of what neural nets were doing, NN research wouldn't be getting anywhere. But that's obviously not the case.

More to the point, there's promising-looking work going on at getting a better understanding of what various NNs actually represent. Deep learning networks might actually have relatively human-comprehensible features on some of their levels (see e.g. the first link).

Furthermore it's not clear that any other human-level machine learning model would be any more comprehensible. Worst case, we have something like a billion variables in a million dimensions: good luck trying to understand how that works, regardless of whether it's a neural network or not.