Generative artificial intelligence is increasingly shaping the content people encounter in everyday life, from text-based outputs to visual representations. While GenAI offers many opportunities, it can also reproduce societal biases. Drawing on the Stereotype Content Model, this study examines gender stereotypes of warmth and competence in AI-generated ratings, stories, and images compared to human-generated content.

Our study shows that women are portrayed as warmer and less competent than men in ChatGPT ratings and DALL·E images, and that these differences are even stronger than in comparable human-generated content. Highlighting that gender-stereotypical differences may not only be mirrored but amplified in AI-generated content, our findings have crucial implications for policymakers, developers, and users of GenAI.

• The full paper is available here:
  Wölfle, A., & Schmuck, D. (2026). Are bots more biased than humans? Assessing gender stereotypes of warmth and competence in AI-generated ratings, stories, and images. Computers in Human Behavior Reports, 23, 101145. https://doi.org/10.1016/j.chbr.2026.101145