UWaterloo researchers develop new method to detect hate speech on social media

The school says that Multi-Modal Discussion Transformer , which is currently working at an 88 per cent accuracy rate, will make life easier for those who are tasked with flagging hate speech.

“We believe that by taking a community-centred approach in our applications of AI, we can help create safer online spaces for all.”The school says the mDT can understand the relationship between text and images while also reasoning the greater context surrounding comments.The program also reduces the number of false positives as it can deduce comments which have been incorrectly flagged as hate speech because they contain culturally sensitive language.

“Understanding that distinction is easy for humans, but training a model to understand the contextual connections in a discussion, including considering the images and other multimedia elements within them, is a very hard problem.”

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