Documenting Patterns of Exoticism of Marginalized Populations within Text-to-Image Generators

TL;DR

This paper investigates how text-to-image generators exoticize marginalized populations, especially from the Global South, revealing patterns of cultural overamplification and its implications for harm-aware AI development.

Contribution

It extends previous work on exoticism to analyze diverse global populations, highlighting biases in generated images and proposing community-centered improvements for GAI tools.

Findings

Global South images show cultural overamplification in attire

Exoticism patterns are present in Western and marginalized populations

Implications for harm-aware and community-centered GAI design

Abstract

A significant majority of AI fairness research studying the harmful outcomes of GAI tools have overlooked non-Western communities and contexts, necessitating a stronger coverage in this vein. We extend our previous work on exoticism (Ghosh et al., 2024) of 'Global South' countries from across the world, as depicted by GAI tools. We analyze generated images of individuals from 13 countries -- India, Bangladesh, Papua New Guinea, Egypt, Ethiopia, Tunisia, Sudan, Libya, Venezuela, Colombia, Indonesia, Honduras, and Mexico -- performing everyday activities (such as being at home, going to work, getting groceries, etc.), as opposed to images for the same activities being performed by persons from 3 'Global North' countries -- USA, UK, Australia. While outputs for 'Global North' demonstrate a difference across images and people clad in activity-appropriate attire, individuals from 'Global South' countries are depicted in similar attire irrespective of the performed activity, indicative of a pattern of exoticism where attire or other cultural features are overamplified at the cost of accuracy. We further show qualitatively-analyzed case studies that demonstrate how exoticism is not simply performed upon 'Global South' countries but also upon marginalized populations even in Western contexts, as we observe a similar exoticization of Indigenous populations in the 'Global North', and doubly upon marginalized populations within 'Global South' countries. We document implications for harm-aware usage patterns of such tools, and steps towards designing better GAI tools through community-centered endeavors.