No, not really. The "structure of the world" such nets learn is based on bottom-up processing of data -- moving from basic features such as orientations and colours to more complex features. As a result it will make famously absurd predictions like mistake a spotty fur coat for an actual leopard, since it has no "model" of a leopard, in the sense people go "this is an absurd place for a leopard to sit so it's most ceratinly a fur coat rather than an animal". Or to use use a more technical term, no prior probability of a leopard given observed data. Hence a standard convnet (if there is such a thing) will massively overestimate the probabilities of such "adversial" stimuli.