What Working On Artificial Intelligence Is Teaching Us About Learning

“These networks clearly aren’t cheating in the way that the digesting duck was. But does all this biological inspiration mean that they work like the brain? One way to approach this question is to look more closely at their performance. To this end, scientists are studying ‘adversarial examples’ – real images that programmers alter so that the machine makes a mistake. Very small tweaks to images can be catastrophic: changing a few pixels on an image of a teapot, for example, can make the network label it an ostrich. It’s a mistake a human would never make, and suggests that something about these networks is functioning differently from the human brain.”