Across 500,000 observations Thema Monroe-White and her colleagues observe generated outputs from the base models of five publicly available language models (ChatGPT 3.5, ChatGPT 4, Claude 2.0, Llama 2, and PaLM 2) are more likely to omit characters with minoritized race, gender, and/or sexual orientation identities compared to reported levels in the U.S. Census, or relegate them to subordinated roles as opposed to dominant ones. They also document patterns of stereotyping across language model–generated outputs with the potential to disproportionately affect minoritized individuals.View the research HERE