The Facebook insider building content moderation for the AI era | TechCrunch

When Brett Levenson left Apple in 2019 to lead business integrity at Facebook, the social media giant was in the thick of the Cambridge Analytica fallout. At the time, he thought he could simply fix Facebook’s content moderation problem with better technology.  The problem, he quickly learned, ran deeper than technology. Human reviewers were expected to memorize a 40-page policy document that had been machine-translated into their language, he said. Then they had about 30 seconds per piece of flagged content to decide not just whether that  content violated the rules, but what to do about it: block it, ban the user, limit the spread. Those quick calls were only “slightly better than 50% accurate,” according to Levenson. “It was kind of like flipping a coin, whether the human reviewers could actually address policies correctly, and this was many days after the harm had already occurred anyway,” Levenson told TechCrunch. That sort of delayed, reactive approach is not sustainable in a world of nimble and well-funded adversarial actors. The rise of AI chatbots has only compounded the problem, as content moderation failures have resulted in a string of high-profile incidents, like chatbots providing teens with self-harm guidance or AI-generated imagery evading safety filters. Levenson’s frustration led to the idea of “policy as code” — a way to turn static policy documents into executable, updatable logic tightly coupled to enforcement. That insight led to the founding of Moonb...