Predicting the resiliency “tipping points” of complex natural and social systems
A central underpinning of The Resilient Investor is the recognition that in our increasingly complex world, it’s nearly impossible to predict how the future will unfold. That remains true, but a team of researchers at Northeastern University is using complex non-linear math to try to shed some light on a key modern problem: predicting when a natural or social system will hit a “tipping point” that triggers rapid breakdowns in its natural resiliency:
Using statistical physics, Northeastern network scientist Albert-László Barabási and his colleagues Jianxi Gao and Baruch Barzel have developed a tool to identify that tipping point—for everything from ecological systems such as bees and plants to technological systems such as power grids. It opens the door to planning and implementing preventive measures before it’s too late, as well as preparing for recovery after a disaster.
Then, says Jianxi Gao, one of the researchers who developed the method, “you can begin to tackle how to manipulate that resilience—how to enhance resilience or restore resilience. These are not easy questions, but our theory, by giving us a picture of the entire system, paves the way to the answers.” A video about their work (embedded below) is especially evocative.
While this is only a start, it’s just the sort of previously unimaginable leap of understanding that will likely come more and more frequently as computing power increases, taps into the distributed data now gathering in the cloud, and moves inexorably, though at a still-uncertain pace, into increasingly functional artificial intelligences. Along the way, say resilient investors who favor the Breakthrough/Driver perspective, we’ll find that these kinds of complexity models will become more common, and offer practical insights that have been beyond our grasp.