The reason I relate human skill with DL, is because for tasks where there are real patterns that humans can consistently recognize, DL is applicable, because it

The reason I relate human skill with DL, is because for tasks where there are real patterns that humans can consistently recognize, DL is applicable, because it relies on human labeled inputs. For patterns, even humans can't consistently recognize (or if there are patterns at all), there's no way for DL to be better than humans, simply because the inputs from human can't be trusted. The example of DL does better job at e.g. recognizing dog breeds, recognizing cancers, whatever, is because those jobs are possible for humans to begin with. The only difference there would be DL could work on more human labeled data than any real human, so that they can recognize more patterns. But if those human labeled data/patterns dont exist in the first place, why we would believe DL could do a better job?