AI demonstrates immense capabilities in various fields, from healthcare to industrial optimization, yet it struggles to effectively predict and mitigate natural disasters like floods due to data inadequacies.
The existing climate models fall short when it comes to predicting extreme weather events, with phenomena like heatwaves occurring at a rate more rapid than models project, highlighting discrepancies in forecasting.
Dim Coumou emphasizes that a significant challenge in accurately forecasting floods lies in the rarity of extreme weather events, resulting in limited data to train AI models effectively.
David Baker notes that for AI to be a valuable tool in science, particularly in disaster forecasting, it requires access to extensive, high-quality data, which is often lacking.
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