Generative AI May Prefer to Present National-level Characteristics of Cities Based on Stereotypical Geographic Impressions at the Continental Level

TL;DR

This study reveals that a Chinese generative AI platform tends to produce city images reflecting stereotypes about economic development at the continental level, potentially reinforcing geographic biases.

Contribution

The paper demonstrates that Wenxin Yige generative AI exhibits stereotypical biases in urban imagery, highlighting limitations in diversity and accuracy for geographic representations.

Findings

AI-generated images reflect stereotypes of economic development

Generated images lack diversity of urban landscapes

Potential to reinforce geographic stereotypes in education

Abstract

A simple experiment was conducted to test the ability of the Chinese-based generative artificial intelligence (AI) platform, Wenxin Yige, to render images of urban street views of different countries. The study found that images generated by this AI platform may contain continental-level stereotypes in terms of showing the level of economic development and modernization. Street view images generated from Wenxin Yige do not adequately represent the diverse range of urban landscapes found across different nations. Using these generated images for geography education or outreach initiatives could inadvertently strengthen people's existing stereotypical views about individual countries.