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The Afghanistan earthquake shows the promise and limits of AI

The Afghanistan earthquake shows the promise and limits of AI

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On Wednesday, eastern Afghanistan was ravaged by an earthquake, killing more than 1,000 people and injuring 1,600 others, marking the deadliest earthquake in the country in two decades.

In the days since, search-and-rescue efforts have been hobbled by rain and landslides, closing off towns and villages to ambulances and aid. Residents have been left to dig out their loved ones, houses and prizes from amid the rubble. Children have lost parents overnight.

These are scenarios that artificial intelligence experts focused on disaster management are trying to prevent. In recent years, there’s been a flurry of technology and research attempting to help governments better predict and respond to disasters like floods, tsunamis and earthquakes.

Researchers are using deep-learning algorithms to filter out city noise so earthquake data can be collected better. Algorithms analyze seismic data from previous earthquakes to predict earthquakes earlier and notify people more quickly.

“AI can be very fast — it can give more warning time for people,” said Mostafa Mousavi, an artificial intelligence researcher at Stanford University who specializes in geophysics and earthquakes. “Even ten seconds can save a lot of lives.”

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But the situation in Afghanistan, researchers note, shows the structural challenges artificial intelligence faces in places with crumbling infrastructure.

To learn more, The Washington Post talked with Monique Kuglitsch, chair of a joint U.N. working group focused on AI for natural disaster management, and Mousavi.

This interview has been edited for length and clarity.

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Read full article on www.washingtonpost.com