LLMs Mirror Country-Specific Gender Patterns If Asked, but Skew Male When Generating Media in Local Languages
Large language models (LLMs) are increasingly used to generate media, but whether their content perpetuates gender stereotypes is unknown: standard benchmarks rely on selection-based formats rather than long-form generation, and surveyed baselines for local gender associations are scarce outside the West. We collect gender associations for 22 occupational and domestic roles from 695 respondents across the United States, India, Kenya, and Nigeria, and evaluate eight LLMs under two regimes: direct questioning and media generation. Models track the surveyed associations under direct questioning but skew substantially more male under media generation in major local-language cells, consistent ...
| Authors | Sharif Kazemi, Tanya Popli, Neil K. R. Sehgal et al. |
|---|---|
| Primary category | cs.CL |
| Published | 6 September 2026 |
| Last updated at source | 6 September 2026 |
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