This is part of the data recipe for Facebook's new large language model, which the company claims is able to detect and rein in harmful content in over 100 languages. Bumble uses similar technology to detect rude and unwanted messages in at least 15 languages. Google uses it for everything from translation to filtering newspaper comment sections. All have comparable recipes and the same dominant ingredient: English-language data. For years, social media companies have focused their automatic content detection and removal efforts more on content in English than the world's 7,000 other languages.

AI looks to be the ideal response to the rising difficulties of content moderation on social media platforms, given the vast amount of data, the frequency of violations, and the need for human judgments without requiring people to make them. We sometimes portray AI content moderation as a necessary response: the enormous size of social media platforms like Facebook and YouTube explains why AI approaches are desirable, if not imperative. Interactive online platforms have grown more important in our daily lives. By eliminating traditional editorial constraints, user-generated content has stimulated dynamic online dialogues, improved business processes, and increased access to information. However, it has also created substantial issues in terms of how to regulate harmful online content.