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Disaster relief is dangerously broken. Can AI fix it?

Posted On November 26, 2018

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In 2014, Stanford student structural engineer Ahmad Wani was visiting family in his native Kashmir when a catastrophic flood struck. The rising waters stranded him and his family for seven days without food or water, during which they watched their neighbor’s home collapse, killing everyone inside.


After this horrifying experience, Wani was struck by just how disorganized the emergency response was. “There is no science behind how people should be rescued,” he says. “Disaster response is really random.”

Today, Wani’s startup One Concern is launching a machine learning platform that provides cities with specialized maps to help emergency crews decide where to focus their efforts in a flood. The maps update in real-time based on data about where water is flowing to estimate where people need help the most. It’s the latest in a wave of AI-powered tools aimed at helping cities prepare for an era of severe, and increasingly frequent, disasters.

Since 1980, the U.S. has suffered from 219 climate disasters that cost over $1 billion, with the total cost exceeding $1.5 trillion. In 2017 alone, these disasters cost the country $306 billion. Since 2000, more than 1 million people have perished from these extreme weather events. As climate change heralds more devastating natural disasters, cities will need to rethink how they plan for and respond to disasters. Artificial intelligence, such as the platform One Concern has developed, offers a tantalizing solution. But it’s new and largely untested. And the urgency is growing by the day.