Template:Complicated capsule: Difference between revisions

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'''[[Complicated system]]s''': Unlike [[simple system]]s, [[complicated system]]s need skilled management and some [[subject matter expert|expertise]] to operate — a school leaver in Bucharest with plenty of coffee and a [[playbook]] on her lap probably isn’t the droid you’re looking for — but in the right hands can usually be managed without catastrophe, though the degree of success will be a function of the degree of expertise. You know you have a [[complicated system]] when it cleaves to a comprehensive set of axioms and rules, and thus it is a matter of making sure that the proper models are being used for the situation at hand. [[Chess]] and [[Alpha Go]] are [[Complicated system|complicated]], but not [[Complex systems|complex]], systems. You can “force-solve” them, at least in theory.<ref>Do you hear that, {{author|Daniel Susskind}}?</ref> They are entirely predictable, determinative and calculable, given enough processing power. They’re [[tame problem|tame]], ''not'' [[wicked problem]]s.
[[Complicated system]]s require interaction with autonomous agents whose specific behaviour is beyond the observer’s control, and might be intended to defeat the observer’s objective, but whose ''range'' of behaviour is deterministic, rule-bound and [[known]] and can be predicted in advance, and where the observer’s observing behaviour does not itself interfere with the essential equilibrium of the system.  
 
You know you have a [[complicated system]] when it cleaves to a comprehensive set of axioms and rules, and thus it is a matter of making sure that the proper models are being used for the situation at hand. [[Chess]] and [[Alpha Go]] are [[Complicated system|complicated]], but not [[Complex systems|complex]], systems. So are most sports. You can “force-solve” them, at least in theory.
 
[[Complicated system]]s benefit from skilled management and ''some'' [[subject matter expert|expertise]] to operate: a good chess player will do better than a poor one, and clearly a skilled, fit footballer can execute a plan better than a wheezy novice — but in the right hands and given good instructions even a mediocre player can usually manage without catastrophe. While success will be partly a function of user’s skill and expertise, a bad player with a good plan may defeat a skilled player with a bad one.
 
Given enough processing power, complicated systems are predictable, determinative and calculable. They’re [[tame problem|tame]], ''not'' [[wicked problem]]s.

Latest revision as of 03:02, 8 August 2023

Complicated systems require interaction with autonomous agents whose specific behaviour is beyond the observer’s control, and might be intended to defeat the observer’s objective, but whose range of behaviour is deterministic, rule-bound and known and can be predicted in advance, and where the observer’s observing behaviour does not itself interfere with the essential equilibrium of the system.

You know you have a complicated system when it cleaves to a comprehensive set of axioms and rules, and thus it is a matter of making sure that the proper models are being used for the situation at hand. Chess and Alpha Go are complicated, but not complex, systems. So are most sports. You can “force-solve” them, at least in theory.

Complicated systems benefit from skilled management and some expertise to operate: a good chess player will do better than a poor one, and clearly a skilled, fit footballer can execute a plan better than a wheezy novice — but in the right hands and given good instructions even a mediocre player can usually manage without catastrophe. While success will be partly a function of user’s skill and expertise, a bad player with a good plan may defeat a skilled player with a bad one.

Given enough processing power, complicated systems are predictable, determinative and calculable. They’re tame, not wicked problems.