To Break a Hate Speech Detection Algorithm, Try 'Love'

For all the advances being made in the field, artificial intelligence still struggles when it comes to identifying hate speech. When he testified before Congress in April, Facebook CEO Mark Zuckerberg said it was "one of the hardest" problems. But, he went on, he was optimistic that "over a five- to 10-year period, we will have AI tools that can get into some of the linguistic nuances of different types of content to be more accurate in flagging things for our systems." For that to happen, however, humans will need first to define for ourselves what hate speech means--and that can be hard because it's constantly evolving and often dependent on context. "Hate speech can be tricky to detect since it is context and domain dependent. Trolls try to evade or even poison such [machine learning] classifiers," says Aylin Caliskan, a computer science researcher at George Washington University who studies how to fool artificial intelligence.