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We study stereotypes embedded within one of the most popular text-to-imagegenerators: Stable Diffusion. We examine what stereotypes of gender andnationality/continental identity does Stable Diffusion display in the absenceof such information i.e. what gender and nationality/continental identity isassigned to `a person', or to `a person from Asia'. Using vision-language modelCLIP's cosine similarity to compare images generated by CLIP-based StableDiffusion v2.1 verified by manual examination, we chronicle results from 136prompts (50 results/prompt) of front-facing images of persons from 6 differentcontinents, 27 nationalities and 3 genders. We observe how Stable Diffusionoutputs of `a person' without any additional gender/nationality informationcorrespond closest to images of men and least with persons of nonbinary gender,and to persons from Europe/North America over Africa/Asia, pointing towardsStable Diffusion having a concerning representation of personhood to be aEuropean/North American man. We also show continental stereotypes and resultantharms e.g. a person from Oceania is deemed to be Australian/New Zealander overPapua New Guinean, pointing to the erasure of Indigenous Oceanic peoples, whoform a majority over descendants of colonizers both in Papua New Guinea and inOceania overall. Finally, we unexpectedly observe a pattern ofoversexualization of women, specifically Latin American, Mexican, Indian andEgyptian women relative to other nationalities, measured through an NSFWdetector. This demonstrates how Stable Diffusion perpetuates Westernfetishization of women of color through objectification in media, which if leftunchecked will amplify this stereotypical representation. Image datasets aremade publicly available.

'Person' == Light-skinned, Western Man, and Sexualization of Women of Color: Stereotypes in Stable Diffusion