A Video-Game Algorithm to Solve Online Abuse

One challenge the system faces is discerning context. As in any team sport, players often build camaraderie through joshing or sarcasm that, in another context, could be deemed unkind or aggressive. A machine usually fails to catch the sarcasm. In fact, that is perhaps the most significant barrier to fighting online abuse with machine learning. “It is pretty fair to say that AIs that understand language perform best when minimal contextual information is necessary to compute the correct response,” explains Chris Dyer, an assistant professor at Carnegie Mellon University who works on natural language processing. “Problems that require integrating a lot of information from the context in which an utterance is made are much harder to solve, and sarcasm is extremely context dependent.”