The Ethics of AI-Generated Maps: A Study of DALLE 2 and Implications for Cartography
Not on the map. Why?
Abstract (arXiv)
The rapid advancement of artificial intelligence (AI) such as the emergence of large language models including ChatGPT and DALLE 2 has brought both opportunities for improving productivity and raised ethical concerns. This paper investigates the ethics of using artificial intelligence (AI) in cartography, with a particular focus on the generation of maps using DALLE 2. To accomplish this, we first create an open-sourced dataset that includes synthetic (AI-generated) and real-world (human-designed) maps at multiple scales with a variety settings. We subsequently examine four potential ethical concerns that may arise from the characteristics of DALLE 2 generated maps, namely inaccuracies, misleading information, unanticipated features, and reproducibility. We then develop a deep learning-based ethical examination system that identifies those AI-generated maps. Our research emphasizes the importance of ethical considerations in the development and use of AI techniques in cartography, contributing to the growing body of work on trustworthy maps. We aim to raise public awareness of the potential risks associated with AI-generated maps and support the development of ethical guidelines for their future use.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 Apr 2023.
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Citing papers per year: 2023: 6.
6 papers.
- 2023A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validationcited by 93
- 2023Building Privacy-Preserving and Secure Geospatial Artificial Intelligence Foundation Modelscited by 12
- 2023Transformation vs Tradition: Artificial General Intelligence (AGI) for Arts and Humanitiescited by 9
- 2023Artificial Intelligence Studies in Cartography: A Review and Synthesis of Methods, Applications, and Ethicscited by 4
- 2023Understanding Place Identity with Generative AIcited by 1
- 2023Generative AI May Prefer to Present National-level Characteristics of Cities Based on Stereotypical Geographic Impressions at the Continental Levelcited by 1
- 2023Artificial Intelligence Studies in Cartography: A Review and Synthesis of Methods, Applications, and Ethics13 Dec 2023
- 2023Transformation vs Tradition: Artificial General Intelligence (AGI) for Arts and Humanities30 Oct 2023
- 2023Generative AI May Prefer to Present National-level Characteristics of Cities Based on Stereotypical Geographic Impressions at the Continental Level7 Oct 2023
- 2023Building Privacy-Preserving and Secure Geospatial Artificial Intelligence Foundation Models29 Sep 2023
- 2023Understanding Place Identity with Generative AI7 Jun 2023
- 2023A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation19 May 2023