Urban Chatter: Exploring the Potential of ChatGPT-like and Generative AI in Enhancing Planning Support

Huaxiong Jiang*, Mengjuan Li, Patrick Witte*, Stan Geertman*, Haozhi Pan*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Historically, Planning Support Systems (PSS) have grappled with an implementation gap stemming from a mismatch between supply and demand. Despite the growing availability of diverse and potentially beneficial planning support tools, practitioners exhibit reluctance in purchasing, implementing, or utilizing them. This phenomenon raises significant questions regarding the perceived value of these readily accessible tools. This paper evaluates the potential of emerging ChatGPT-like and generative AI models in addressing PSS gaps and enhancing planning support in AI urbanism. It reviews literature and considers recent technological advancements, emphasizing implications for urban planning. ChatGPT-like models show promise in improving PSS quality by improving data processing, creative generation, and decision support, and promoting user acceptance through increased public engagement, outreach, and superior communication and education. This enhancement would improve the selectivity in applying planning support technologies in actual planning practice and extend beyond the implementation gap. However, overcoming challenges like data privacy, bias, and feasibility is vital. Urban planners and policymakers are encouraged to adopt these AI models while addressing PSS challenges through research, equitable integration, and responsible practices.
Original languageEnglish
Article number105701
Number of pages8
JournalCities
Volume158
Early online date8 Jan 2025
DOIs
Publication statusPublished - Mar 2025

Bibliographical note

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© 2025 Elsevier Ltd

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