suppose, hypothetically, that a layer already represents a better than random model of how the next layer sees it. perhaps it has multiple hypotheses. suppose also that the layer having a more accurate model is useful for the model to get reward / lower loss. then backprop should leverage information from how the next layer actually saw it to improve its model, right?
if you think this doesn't happen in practice, why not?