Work

Imagining the Far East: Exploring Perceived Biases in AI-Generated Images of East Asian Women

Year: 2025

Type: conference-paper

Abstract: Image-generating AI, which allows users to create images from text, is increasingly used to produce visual content.Despite its advancements, cultural biases in AI-generated images have raised significant concerns.While much research has focused on issues within Western contexts, our study examines the perceived biases regarding the portrayal of East Asian women.In this exploratory study, we invited East Asian users to audit three popular models (DALL-E, Midjourney, Stable Diffusion) and identified 18 specific perceived biases, categorized into four patterns: Westernization, overuse or misuse of cultural symbols, sexualization & feminization, and racial stereotypes.This work highlights the potential challenges posed by AI models in portraying Eastern individuals.

Source: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA)

DOI: 10.1145/3706599.3719678

Authors: Xingyu Lan, Jiaxi An, Yisu Guo, Tong Chiyou, Xintong Cai, Jun Zhang

Institutions: Fudan University, University of California, Los Angeles, Hong Kong Polytechnic University, Hubei Institute of Fine Arts

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

SDG: Reduced inequalities

Open Access status: bronze

Funders: National Natural Science Foundation of China, Fudan University, Shanghai Municipal Education Commission