The social world is carved into a complex variety of groups each associated with unique
stereotypes that persist and shift over time. Innovations in natural language processing …

Today, many social groups face negative stereotypes. Is such negativity a stable feature of
society and, if so, what mechanisms maintain stability both within and across group targets …

What concepts do people use to construct narratives about how to get ahead in
contemporary society? To what extent do these narratives reflect distinctive constellations of …

Highlights•The main content of animals' stereotypes is identified.•The animal stereotype
approach complements animalized dehumanization.•Dehumanization focuses on animals' …

Stereotype benchmark datasets are crucial to detect and mitigate social stereotypes about
groups of people in NLP models. However, existing datasets are limited in size and …

People belong to multiple social groups simultaneously. However, much remains to be
learned about the rich semantic perceptions of multiply-categorized targets. Two pretests …

As text-to-image systems continue to grow in popularity with the general public, questions
have arisen about bias and diversity in the generated images. Here, we investigate …

Following on recent advances in large language models (LLMs) and subsequent chat
models, a new wave of large vision-language models (LVLMs) has emerged. Such models …

As machine learning applications proliferate, we need an understanding of their potential for
harm. However, current fairness metrics are rarely grounded in human psychological …

People see societal groups as less moral, warm, and likable if their ideology is more
dissimilar to the ideology of the self (ie, ideological prejudice). We contribute to the debate …