New AI algorithm can predict the 'tipping points' for future disasters, scientists say

Computer scientists have created an artificial intelligence (AI) program that can predict the onset of catastrophic tipping points — and they want to use it to forecast ecological collapse, financial crashes, pandemics and power outages.

"If an upcoming critical transition can be forecast then we can prepare for the shift or perhaps even prevent the transition, and thus mitigate damage," senior study author Gang Yan, a professor of computer Science at Tongji University in China, told Live Science. "This motivated us to develop an AI approach to predict the onset of such sudden transitions far before it happens."

The researchers published their findings July 15 in the journal Physical Review X

Tipping points are sudden shifts beyond which a localized system, or its environment, changes to an undesirable state from which it is difficult to return. For instance, if the Greenland ice sheet were to collapse, it would also reduce snowfall in the northern part of the island, drastically raising sea levels and making large parts of the sheet irretrievable.

Yet the science behind these dramatic transformations is poorly understood and often based on oversimplified models, making accurate predictions difficult. Previously, scientists used statistics to gauge the diminishing strength and resilience of systems by their growing fluctuations. But the results from studies that use such statistical methods are controversial.

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To search for a more precise way to predict dangerous transitions, the researchers behind the new study combined two different types of neural networks, or algorithms that mimic the way information is processed in the brain. The first broke down complex systems into large networks of interacting nodes before tracking the connections between the nodes; and the second followed how individual nodes changed over time.