“One of the insights in my research at the Max Planck Institute is that if you have a situation that is stable and well defined, then complex algorithms such as deep neural networks are certainly better than human performance. Examples are [the games] chess and Go, which are stable. But if you have a problem that is not stable—for instance, you want to predict a virus, like a coronavirus—then keep your hands off complex algorithms. [Dealing with] the uncertainty—that is more how the human mind works, to identify the one or two important cues and ignore the rest. In that type of ill-defined problem, complex algorithms don’t work well. I call this the “stable world principle,” and it helps you as a first clue about what AI can do. It also tells you that, in order to get the most out of AI, we have to make the world more predictable.”
A Psychologist Explains How AI and Algorithms Are Changing Our Lives
https://www.wsj.com/articles/algorithms-ai-humanity-psychology-ebf1364c
via Instapaper