Last week, a group of AI researchers published a paper outlining a method to defeat KataGo by using adversarial techniques that take advantage of KataGo's blind spots.By playing unexpected moves outside of KataGo's training set, a much weaker adversarial Go-playing program (that amateur humans can defeat) can trick KataGo into losing.Gleave explains that, during a Go match, the adversarial policy works by first staking claim to a small corner of the board.As the paper explains, "The adversary gets points for its corner territory (devoid of victim stones) whereas the victim [KataGo] does not receive points for its unsecured territory because of the presence of the adversary's stones."Imagine a self-driving car AI that encounters a wildly unlikely scenario it doesn't expect, allowing a human to trick it into performing dangerous behaviors, for example."