When users report hate speech, automated "classifiers" - a database created by humans which annotates different kinds of speeches - vet them before selected ones reach human moderators, which are often third-party contractors. "If these classifiers were good enough they would catch a lot more hate speech, with fewer false positives. But they clearly aren't," says Mr Sinha.

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