The "fragmented" coordination between relief actors in the Philippines following Typhoon Haiyan last month underscores the need for artificial intelligence to streamline disaster response, says a team behind such an effort. The ORCHID project, a consortium of UK universities and private firms, aims to make this possible by combining human and artificial intelligence into an efficient complementary unit known as a Human Agent Collective (HAC).
The "fragmented" coordination between relief actors in the Philippines following Typhoon Haiyan last month underscores the need for artificial intelligence to streamline disaster response, says a team behind such an effort. The ORCHID project, a consortium of UK universities and private firms, aims to make this possible by combining human and artificial intelligence into an efficient complementary unit known as a Human Agent Collective (HAC).
!ADVERTISEMENT!
The computer systems being developed can assume tasks such as directing surveillance drones, resource management and search planning, says David Jones, head of Rescue Global, the disaster response organization responsible for testing the software next year.
"Coordination of such a large response [after a disaster] is so challenging without technological assistance that makes data more accessible," he says on mission in the Philippines.
"Bringing humans and artificial intelligence together is the only way to get the job done better."
Computers' data-crunching abilities mean they are good at making sense of the huge amounts of information generated during an emergency from local status reports, social media, and the array of organizations involved in the relief effort.
By collecting and analyzing these data, HAC systems can flexibly implement a number of activities vital for disaster response, says Jones.
These include planning the flight paths of surveillance drones, verifying the authenticity of information coming in from social media, facilitating data sharing and organizing human teams based on their skill sets and current needs on the ground.
Machines not only complete many of these jobs better than humans, but by taking on these complex calculations they allow experts to concentrate on more nuanced tasks such as analyzing the content of photographs or video, and strategic planning.
For HAC systems to be successful, this division of labor must be accounted for and the right balance found between artificial and human input, says Sarvapali Ramchurn, ORCHID applications theme leader from the UK-based University of Southampton.
He believes that the field trials in the Bay of Bengal planned for next year will go a long way towards showing how effective HACs can be, and pave the way for a big impact in the future.
Although exact details of the tests have not been finalized, how the complex algorithms cope with analyzing environmental data coming in from sensors and social media, as well as their ability to assess the quality of this information will likely be scrutinized, he says.
Read more at SciDev.Net.
Robot disaster assistant and flood disaster images via Shutterstock; combined and morphed by Robin Blackstone.
