Generative AI May Prefer to Present National-level Characteristics of Cities Based on Stereotypical Geographic Impressions at the Continental Level
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 9 of its 20 references that are in the map. First posted on arXiv 7 Oct 2023.
Builds on
9 of 20 references.
References · 9
- 2015Deep Residual Learning for Image Recognitioncited by 51,809
- 2023ChatGPT is not all you need. A State of the Art Review of large Generative AI modelscited by 85
- 2023GPT4GEO: How a Language Model Sees the World's Geographycited by 68
- 2020Biases in Generative Art -- A Causal Look from the Lens of Art Historycited by 26
- 2021Hi, my name is Martha: Using names to measure and mitigate bias in generative dialogue modelscited by 23
- 2023Toward General Design Principles for Generative AI Applicationscited by 20
- 2023The Ethics of AI-Generated Maps: A Study of DALLE 2 and Implications for Cartographycited by 6
- 2023Understanding Place Identity with Generative AIcited by 1
- 2023ChatGPT is not a pocket calculator -- Problems of AI-chatbots for teaching Geographycited by 1
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