Report: Agencies Should Turn to AI Before Disaster Strikes

Report: Agencies Should Turn to AI Before Disaster Strikes

NASA-funded researchers applied artificial intelligence to Facebook user location data captured as two fires wrecked northern California in 2018 and gained new insight into people’s evacuation movements and behaviors when disaster strikes, which could strengthen future response. The Defense Innovation Unit and Carnegie Mellon University’s Software Engineering Institute are collectively crafting datasets to teach AI tools to assess buildings and structures after natural crises occur, and ultimately augment and increase the accuracy of damage estimates.


These are two of many examples detailed in a new report from the Partnership for Public Service and Microsoft that explores how the maturing technology can improve disaster resilience and response, and considerations and actions governments should pursue when adopting AI to boost preparedness, recovery and relief. The report suggests agencies improve data collection and access, make proactive instead of reactive moves, collaborate with other organizations—and more.


“While some governments, companies and universities have already used AI in this field, most are still in the early stages of use,” officials wrote in the report. “However, AI technologies could contribute to disaster preparation and response better than any other technology or innovation in operation now.”


The organizations interviewed 23 employees with relevant experience from either federal, state and local government, academic institutions, or private sector insights and also examined scientific studies and government preparedness plans to inform the report. “It’s notable how well-suited AI is to improving disaster resilience, and AI’s impact on disaster resilience could be substantial and positive,” Partnership for Public Service Vice President Katie Malague told Nextgov Friday.


“Disaster resilience is heavily dependent on information collection, analysis and dissemination, and those are areas in which AI tools made great advancements over the past two or so decad ..

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