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Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GIScience.2023.41
URN: urn:nbn:de:0030-drops-189363
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2023/18936/
Jang, Kee Moon ;
Chen, Junda ;
Kang, Yuhao ;
Kim, Junghwan ;
Lee, Jinhyung ;
Duarte, Fábio
Understanding Place Identity with Generative AI (Short Paper)
Abstract
Researchers are constantly leveraging new forms of data to understand how people perceive the built environment and the collective place identity of cities. Latest advancements in generative artificial intelligence (AI) models have enabled the creation of realistic representations of real-world settings. In this study, we explore the potential of generative AI as the source of textual and visual information in capturing the place identity of cities assessed by filtered descriptions and images. We asked questions on the place identity of a set of 31 global cities to two generative AI models, ChatGPT and DALL·E2. Since generative AI has raised ethical concerns regarding its trustworthiness, we performed cross-validation to examine whether the results show similar patterns to real urban settings. In particular, we compared the outputs with Wikipedia data for text and images searched from Google for images. Our results indicate that generative AI models have the potential to capture the collective features of cities that can make them distinguishable. This study is among the first attempts to explore the capabilities of generative AI in understanding human perceptions of the built environment. It contributes to urban design literature by discussing future research opportunities and potential limitations.
BibTeX - Entry
@InProceedings{jang_et_al:LIPIcs.GIScience.2023.41,
author = {Jang, Kee Moon and Chen, Junda and Kang, Yuhao and Kim, Junghwan and Lee, Jinhyung and Duarte, F\'{a}bio},
title = {{Understanding Place Identity with Generative AI}},
booktitle = {12th International Conference on Geographic Information Science (GIScience 2023)},
pages = {41:1--41:6},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-288-4},
ISSN = {1868-8969},
year = {2023},
volume = {277},
editor = {Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2023/18936},
URN = {urn:nbn:de:0030-drops-189363},
doi = {10.4230/LIPIcs.GIScience.2023.41},
annote = {Keywords: ChatGPT, DALL·E2, place identity, generative artificial intelligence, sense of place}
}
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Keywords: |
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ChatGPT, DALL·E2, place identity, generative artificial intelligence, sense of place |
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Collection: |
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12th International Conference on Geographic Information Science (GIScience 2023) |
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Issue Date: |
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2023 |
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Date of publication: |
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07.09.2023 |
