Facebook AI Blog: “…In order for AI to become a more effective tool for detecting hate speech, it must be able to understand content the way people do: holistically. When viewing a meme, for example, we don’t think about the words and photo independently of each other; we understand the combined meaning together. This is extremely challenging for machines, however, because it means they can’t just analyze the text and the image separately. They must combine these different modalities and understand how the meaning changes when they are presented together. To catalyze research in this area, Facebook AI has created a data set to help build systems that better understand multimodal hate speech. Today, we are releasing this Hateful Memes data set to the broader research community and launching an associated competition, hosted by DrivenData with a $100,000 prize pool. The challenges of harmful content affect the entire tech industry and society at large. As with our work on initiatives like the Deepfake Detection Challenge and the Reproducibility Challenge, Facebook AI believes the best solutions will come from open collaboration by experts across the AI community…”

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