  We study stereotypes embedded within one of the most popular text-to-image
generators: Stable Diffusion. We examine what stereotypes of gender and
nationality/continental identity does Stable Diffusion display in the absence
of such information i.e. what gender and nationality/continental identity is
assigned to `a person', or to `a person from Asia'. Using vision-language model
CLIP's cosine similarity to compare images generated by CLIP-based Stable
Diffusion v2.1 verified by manual examination, we chronicle results from 136
prompts (50 results/prompt) of front-facing images of persons from 6 different
continents, 27 nationalities and 3 genders. We observe how Stable Diffusion
outputs of `a person' without any additional gender/nationality information
correspond closest to images of men and least with persons of nonbinary gender,
and to persons from Europe/North America over Africa/Asia, pointing towards
Stable Diffusion having a concerning representation of personhood to be a
European/North American man. We also show continental stereotypes and resultant
harms e.g. a person from Oceania is deemed to be Australian/New Zealander over
Papua New Guinean, pointing to the erasure of Indigenous Oceanic peoples, who
form a majority over descendants of colonizers both in Papua New Guinea and in
Oceania overall. Finally, we unexpectedly observe a pattern of
oversexualization of women, specifically Latin American, Mexican, Indian and
Egyptian women relative to other nationalities, measured through an NSFW
detector. This demonstrates how Stable Diffusion perpetuates Western
fetishization of women of color through objectification in media, which if left
unchecked will amplify this stereotypical representation. Image datasets are
made publicly available.
