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DTSTART;TZID=America/Toronto:20250421T150000
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URL:https://uwaterloo.ca/future-cities-institute/events/ai-powered-solution
 s-bridging-urban-climate-policy-data-gaps
LOCATION:Balsillie School of International Affairs (67 Erb St. W\, Waterloo
 \, ON N2L 6C2). Canada
SUMMARY:AI-Powered Solutions for Bridging Urban Climate Policy Data Gaps
CLASS:PUBLIC
DESCRIPTION:ANGEL HSU\nMachine learning\, generative AI\, including Large L
 anguage Models\n(LLMs) hold immensepotential in addressing critical data a
 nd\ninformation gaps within city climate policy. Thesetechnologies enable\
 ncities to estimate greenhouse gas emission sources\, identify\nenvironmen
 talhotspots\, evaluate policy performance trends\, and\ncomprehend the div
 erse impacts of climatechange. This presentation\nwill showcase several ca
 se studies that illustrate how\nAI-drivenapproaches can innovate data coll
 ection\, analysis\, and policy\nformulation in the context of urbanclimate
  management\, including\nevaluating net-zero climate policy and strategy w
 ith LLMs andtopic\nmodeling\, distributional climate and environmental imp
 acts within\nurban areas\, theintegration of satellite remote sensing for\
 nparticipatory heat-stress mapping\, among otherexamples. It will also\ndi
 scuss some of the challenges and pitfalls of applying AI to urban\nclimate
 policy and management\, such as the \"black box\" AI problem and\nbiases o
 f underlying trainingdata.
DTSTAMP:20260501T202358Z
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