In my experience people will come at this from a variety viewpoints. Typically they (1) don't trust the model to learn something useful, so they want some confidence that the model isn't going to do exotic things with new inputs (i.e. they want some faith in the generalization ability of the model to unseen inputs) or (2) they want the model to help them understand the problem. Your language example is perfect. How nice would it be for linguistics if a complex model could tell you about simple structures that you didn't previously know about. It is nearly an article of faith with some people that these simple structures must be there generating the statistics we see, like they haven't considered the possibility that there might not be a simple structure underneath.