Facebook Trains AI on ‘Hateful Memes’

Facebook unveiled an initiative Tuesday to take on “hateful memes” by using artificial intelligence, backed by crowd sourcing, to identify maliciously motivated posts.

The leading social network said it had already created a database of 10,000 memes — images often blended with text to deliver a specific message — as part of a ramped-up effort against hate speech.

Facebook said it was releasing the database to researchers as part of a “hateful memes challenge” to develop improved algorithms to detect hate-driven visual messages, with a prize pool of $100,000.

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Its quarterly transparency report said Facebook removed some 9.6 million posts for violating “hate speech” policies in the first three months of this year, including 4.7 million pieces of content “connected to organized hate.”

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Heather Woods, a Kansas State University professor who studies memes and extremist content, welcomed Facebook’s initiative and inclusion of outside researchers.

“Memes are notoriously complex, not only because they are multimodal, incorporating both image and text, as Facebook notes, but because they are contextual,” Woods said.

“I imagine memes’ nuance and contextual specificity will remain a challenge for Facebook and other platforms looking to weed out hate speech.”