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<p>Cities are changing faster than the tools used to understand them. A new generation of AI can now synthesize images, model aspects of human behavior and reason across heterogeneous data—capabilities that are beginning to reshape how researchers and practitioners observe, model and support decisions about urban life. Here, in this Review, we explore what these tools can genuinely offer, where the evidence is strong and where it remains thin. The answer depends less on technical novelty than on whether generative AI can be evaluated honestly, validated in context and deployed in ways that keep human judgment and accountability at the center.</p>

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Generative AI in urban science and practice

  • 期刊论文

  • 发表日期：

    2026年8月5日

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  • Yunke Zhang,
  • Fengli Xu,
  • Qi R. Wang,
  • Esteban Moro,
  • Yang Yue,
  • Huandong Wang,
  • Bin Chen,
  • Yu Liu,
  • Dongping Fang,
  • Peng Gong,
  • Luís M. A. Bettencourt,
  • Michael Batty,
  • Yong Li

摘要

Cities are changing faster than the tools used to understand them. A new generation of AI can now synthesize images, model aspects of human behavior and reason across heterogeneous data—capabilities that are beginning to reshape how researchers and practitioners observe, model and support decisions about urban life. Here, in this Review, we explore what these tools can genuinely offer, where the evidence is strong and where it remains thin. The answer depends less on technical novelty than on whether generative AI can be evaluated honestly, validated in context and deployed in ways that keep human judgment and accountability at the center.