Information from the abstract
Artificial intelligence (AI) holds transformative potential to decode urban climate resilience (UCR) complexities, yet its unguided expansion risks amplifying systemic biases. Here, we leverage large language models to conduct a systematic analysis of around 12,500 UCR publications from 2005 to 2024. Our findings reveal a fifteenfold increase in AI-related publications since 2018, yet this growth remains geographically concentrated: the United States, China, and the United Kingdom account for ~40% of AI-integrated studies, highlighting a deepening digital divide in both research capacity and geographic focus that limits the transferability of AI models to low-income regions. Crucially, we identify a statistically significant structural imbalance: while AI is heavily deployed for physical hazard prediction (40%), it remains under-represented in governance resilience domains (
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Related topics: Sustainability and Climate Change Governance · Urban Heat Island Mitigation · Smart Cities and Technologies
Thai researcher and institutional participation
Liang Emlyn Yang · Chulalongkorn University
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