MIT's new book 'How AI Sees the City' weighs visual AI's promise and perils for urban studies
MIT News AI · rss · 2026-09-24
Researchers from MIT's Senseable City Lab — Fábio Duarte, Martina Mazzarello, Carlo Ratti and Peking University's Fan Zhang — have published 'How AI Sees the City: Urban Visual Intelligence' (Routledge).
- Applications: ML identifying vehicle types across 331 NYC traffic cameras to estimate emissions; analyzing traffic snarls, intersection safety and public-space usage; measuring everyday 'greenery visibility'; an Airbnb study of 400,000 listings showing interior design styles are not globally homogenizing.
- Intellectual lineage: the authors position visual AI as a continuation of Kevin Lynch's 'The Image of the City' and Whyte's public-space studies — 'Lynch was only using paper and pen; we can now scale that up.'
- Perils: London has 210 cameras per square mile while Shanghai exceeds 5,000; ubiquitous visual surveillance erodes personal freedom, and biased models can reinforce stereotypes about neighborhoods and minority groups — 'AI is not neutral.'
The authors conclude cities should explore visual AI 'wisely, critically, and creatively.'
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