Fighting Hate Speech, Silencing Drag Queens? Artificial Intelligence in Content Moderation and Risks to LGBTQ Voices Online

Dias Oliva, Thiago; Antonialli, Dennys Marcelo; Gomes, Alessandra
Sexuality & Culture

Companies operating internet platforms are developing artificial intelligence tools for content moderation purposes. This paper discusses technologies developed to measure the ‘toxicity’ of text-based content. The research builds upon queer linguistic studies that have indicated the use of ‘mock impoliteness’ as a form of interaction employed by LGBTQ people to cope with hostility. Automated analyses that disregard such a pro-social function may, contrary to their intended design, actually reinforce harmful biases. This paper uses ‘Perspective’, an AI technology developed by Jigsaw (formerly Google Ideas), to measure the levels of toxicity of tweets from prominent drag queens in the United States. The research indicated that Perspective considered a significant number of drag queen Twitter accounts to have higher levels of toxicity than white nationalists. The qualitative analysis revealed that Perspective was not able to properly consider social context when measuring toxicity levels and failed to recognize cases in which words, that might conventionally be seen as offensive, conveyed different meanings in LGBTQ speech.