[lightcatcher]

I'd argue that a neural net is "black-box" in the sense that nobody really can give a coherent answer to "what happens if I perturb/double/negate this parameter" where the parameter might be deep in some weight matrix. Maybe this isn't a useful question because of the distributed representations within neural nets, but it is at least an answerable question for other models.

Do you know of any work on interpreting neural nets that are being used for non-image tasks?