Template:Complex capsule: Difference between revisions
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[[Complex systems]] present as “[[wicked problem]]s”. They are dynamic, unbounded, incomplete, contradictory and constantly changing. They comprise an indefinite set of subcomponents that interact with each other and the environment in unexpected, [[non-linear]] ways. They are thus unpredictable, chaotic and “insoluble” — no [[algorithm]] can predict how they will behave in all circumstances. Probabilistic models may work passably well ''most'' of the time, but the times where statistical models fail may be ''exactly'' the times you really wish they didn’t, as [[Long Term Capital Management]] would tell you. Complex systems may comprise many other [[simple system|simple]], [[complicated system|complicated]] and indeed [[complex system]]s, but their interaction ''with each other'' will be a whole other thing. So while you may manage the [[simple]] and [[complicated]] sub-systems effectively with algorithms, checklists, and playbooks — and may manage tthe system on normal times, you remain at risk to “tail events” in abnormal circumstances. You cannot eliminate this risk: accidents in complex systems are ''inevitable'' — hence “[[Normal accident|normal]]”, in {{author|Charles Perrow}}’s argot. However well you manage a [[complex system]] it remains ''innately'' unpredictable. | |||
Latest revision as of 11:33, 3 April 2022
Complex systems present as “wicked problems”. They are dynamic, unbounded, incomplete, contradictory and constantly changing. They comprise an indefinite set of subcomponents that interact with each other and the environment in unexpected, non-linear ways. They are thus unpredictable, chaotic and “insoluble” — no algorithm can predict how they will behave in all circumstances. Probabilistic models may work passably well most of the time, but the times where statistical models fail may be exactly the times you really wish they didn’t, as Long Term Capital Management would tell you. Complex systems may comprise many other simple, complicated and indeed complex systems, but their interaction with each other will be a whole other thing. So while you may manage the simple and complicated sub-systems effectively with algorithms, checklists, and playbooks — and may manage tthe system on normal times, you remain at risk to “tail events” in abnormal circumstances. You cannot eliminate this risk: accidents in complex systems are inevitable — hence “normal”, in Charles Perrow’s argot. However well you manage a complex system it remains innately unpredictable.