Maybe it's about context. One wouldn't expect to see a (realistic) elephant in a living room. For humans, if something seems "out of place", we tend to focus on

Maybe it's about context. One wouldn't expect to see a (realistic) elephant in a living room. For humans, if something seems "out of place", we tend to focus on it more to make sure we are interpreting it correctly. NN's have no sense of "out of place" other than "knowing" X and Y are not normally seen together in the training set. Humans give oddities "more CPU" (or run like heck to avoid being trampled and worry later about being right). We apply life experience and logic to explore it deeper. In the elephant case, the shadows look wrong also, which should trigger the "Maybe it's a cheap Photoshop job" module in our brain. But NN's don't understand the concept of cheap Photoshop jobs because they don't browse the web for cute kitten videos and fun but fake news like humans do. Maybe NN's can be trained for fake photo detection, but solving every identification hurdle of the human world by adding yet another dimension to the training step probably won't scale.