Here's an example of recurrent neural nets learning intuitive / interpretable representations of some basic aspects of text, like keeping track of quotes and brackets: http://arxiv.org/abs/1506.02078
I know there are many papers that show that neural nets learn features that can in some regimes be given nice interpretations. However in all cases of which I am aware where these representations have been thoroughly analyzed, they seem to fail obvious tests of naturality, which would include things like:
(1) Good performance on different data sets in the same domain.
(2) Good transference to novel domains.
(3) Robustness to visually imperceptible perturbations to the input image.
Moreover, ANNs almost fundamentally cannot learn natural representations because...
New essay summarizing some of my latest thoughts on AI safety, ~3500 words. I explain why I think that some of the thought experiments that have previously been used to illustrate the dangers of AI are flawed and should be used very cautiously, why I'm less worried about the dangers of AI than I used to be, and what are some of the remaining reasons for why I do continue to be somewhat worried.
Backcover celebrity endorsement: "Thanks, Kaj, for a very nice write-up. It feels good to be discussing actually meaningful issues regarding AI safety. This is a big contrast to discussions I've had in the past with MIRI folks on AI safety, wherein they have generally tried to direct the conversation toward bizarre, pointless irrelevancies like "the values that would be held by a randomly selected mind", or "AIs with superhuman intelligence making retarded judgments" (like tiling the universe with paperclips to make humans happy), and so forth.... Now OTOH, we are actually discussing things of some potential practical meaning ;p ..." -- Ben Goertzel