Complex system: Difference between revisions

===You can’t ''eliminate'' the risk, so focus on ''managing'' it===

A traditional risk manager — that is, one managing [[complicated system]]s and not [[complex system|complex]] ones<ref>Open question — a ''gaping'' open question, like when your goalie has come up for a corner — is ''why'' a traditional risk manager is managing what is undoubtedly a [[wicked environment]] using tools suitable for a [[tame environment|tame]] one. But it was ever thus: [[Black-Scholes option pricing model]], which is predicated on a normal distribution, can’t work with The [[Black swan|tail events]] and whose failure in those circumstances led directly to both the [[LTCM]] collapse and the [[Great Financial Crisis]], is still widely used today, after all.</ref> — will be conditioned to using control techniques to anticipate and eliminate all risk.  

You ''cannot'' brute-force compute a [[wicked problem]], like catching a ball,<ref>Ohh, but catching a ball isn’t a wicked problem! I hear you cry. For hard-determinist, reductionist types maybe, but if you have ever pondered the odd lack of tenured physics professors in the national cricket team you may, like the [[JC]] beg to differ. The [[JC]]’s celebrated experiments with [[the proverbial crisp packet in St Mark’s Square]] may help explain.</ref> ''but you can still catch a ball''. Don’t think, “punch all the variables into a machine and run round to the resulting co-ordinate and stick your hand out.”  You don’t have nearly enough information to even make the calculation. Instead, just run towards the damn thing, watching it, adjusting as you go.<ref>A study a while back found professional baseball players, while ''excellent'' at catching moving balls they were allowed to run towards, had a lot more trouble predicting where those balls would land when made to stand still.</ref>

Calculating an exact parabola from initial conditions — even if you have good approximations of the necessary data inputs to hand, which you won’t — will give you a rough vector and distance, but the range of potential trajectories will be far too great to to ever actually catch the ball. Likewise, the prediction of rain in [[Lissingdown]] a month in advance is is highly speculative: we may have average rainfall data, but as to whether it will rain or not at a given moment, who can say?  

This is hard for a [[complicated system]]s guy. [[Complicated system]]s you can brute force, and you can predict how they will behave. You can pre-bake solutions, making them more simple. In [[complex system]]s you can’t: need to keep your options open and be prepared to shift, adapt, re-evaluate, and toss out whatever you might have concluded before now. {{author|Philip Tetlock}}’s “{{br|Superforecasters}}” are complex systems thinkers. Baseball players are complex systems thinkers. Richard Dawkins, whom I like to imagine was dyspraxic,<ref>largely because he was trying to solve differential equations instead of running after the ball, of course.</ref> is a [[complicated system]]s thinker.

Frequently complicated system risk attenuators can, in fact, aggravate risk situations in complex systems. Alarms going off make it harder to hear; multiple alarms increase panic and obscure each other; an obligation to follow prescribed safety routines can impede quick and surgical response to traumatic situations. There are times, therefore, where you want to throw your checklist out the window. <ref>I know, I know — try telling that to the chap who landed his plane on the Hudson thanks to his unflappable compliance with cockpit checklists, right?</ref>

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