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Artificial intelligence in urban science: why does it matter?

Xinyue Ye1, Tan Yigitcanlar2, Michael Goodchild3

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Summary
This summary is machine-generated.

Artificial intelligence (AI) integration in urban science offers opportunities for smarter cities, despite challenges like data and transparency. A symbiotic relationship, termed the New Urban Science, promises equitable and sustainable urban development.

Keywords:
Artificial intelligencedigital twinsexplainable AIhuman dynamicsurban science

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Area of Science:

  • Urban science
  • Artificial intelligence (AI)
  • Sustainability science

Background:

  • Urban science focuses on understanding complex, human-centric systems for sustainability.
  • Integrating artificial intelligence (AI) into urban science faces challenges including data availability, ethics, and model interpretability.
  • AI offers potential for urban management and planning through data analysis, trend prediction, and resilience enhancement.

Purpose of the Study:

  • To explore the challenges and opportunities of integrating AI into urban science.
  • To advocate for a symbiotic relationship between AI and urban science.
  • To introduce the concept of the 'New Urban Science' for developing smarter, equitable, and sustainable cities.

Main Methods:

  • Review of AI applications in urban contexts.
  • Discussion of challenges like data, ethics, and AI interpretability.
  • Exploration of solutions like explainable AI and knowledge-driven approaches.
  • Highlighting reciprocal contributions between AI and urban science.

Main Results:

  • AI can optimize urban infrastructure, predict trends, and enhance resilience using multimodal data.
  • Explainable AI and knowledge-driven methods address transparency concerns in AI models.
  • Urban science provides contextual awareness and human-centric insights to AI development.
  • Digital twins and generative AI are examples of AI integration in urban modeling.

Conclusions:

  • A collaborative, co-learning approach between AI and urban science is essential.
  • The convergence, termed 'New Urban Science,' can lead to more equitable and sustainable urban environments.
  • Aligning AI advancements with urban science goals is key to transformative urban development.