This is about the concept of ‘time approaching zero’, and what the ability to ‘predict the future’ would mean for Risk Management. Whilst the metaphor is easy to grasp with so many smart systems warning us of incoming events, this Wired article grounds the concept in very real science that could have far reaching implications > neuroscientists develop equation for predicting future disasters (and a salute as Aussies from Charles Sturt Uni are involved)
Xavier – 1/11/2013
The article basically says that “the dynamics of complex systems — like the brain and the economy — depend on how their elements causally influence each other; in other words, how information flows between them”. A team at Charles Sturt University in Australia is suggesting it’s possible to measure when a system reaches that tipping point, when an overwhelming number of nodes have caused a change too big to remain stable.
Using supercomputers the team found that one measure called “global transfer entropy flow” reached a peak, repeatedly, “on the disordered side of the transition — just *before* the tipping point”. It’s the density of the information flow that anticipates the tipping point — “all other measures peak strictly at the tipping point itself” – “Financial networks and epilepsy detection, [for example] are canonical examples of phase transitions about critical points”
It also illustrates the importance of entropy when studying complex systems. Entropy is roughly a kind of energy measuring the effluxion of Time, and which always flows in one direction, like water, like time.
To put it in simple words, the entropy of a system left on its own will be higher at 2pm that it was at 1pm. Always. Entropy keeps growing steadily. And we can measure it thanks to all the information contained in that system, right down to the atomic level. And what this research tells us is that if that flow of entropy suddenly peaks, the system is about to change dramatically. A bit like looking at the volume of trades on the stock exchange tells us something is about to go gaga… See the share price of Lehman Brothers during its collapse and its volume of trade as a metaphor for its “entropy flow”, on the pic below.
To be clear, complexity science and mining big data for decision making is now a topic which a plethora of academics and businesses are working on. However they all fall short of claiming to predict the future, and acknowledge the depth of human factors and how they can interfere with mathematically-drawn conclusions. The difference here is that the joint Sussex-Australia team has applied the principles of a known physics model and is only focusing on phase transitions. So if their conjecture holds that a post-critical peak of entropy is a universal phenomenon, it raises promising possibilities of anticipating imminent events in complex systems from markets to brain activity.
And what this research is saying is that if computer can spot those sudden changes just before the tipping point, we might have a way to ‘simulate’ the prediction of the future, and bring time to zero…
The “Entropic Lehmanisation” metaphor in one pic: