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The JC has encountered [[Reductionist|reductionists]] who see [[complexity]] as an [[emergent]] property of even a simple [[algorithm]] of Turing Machine. | The JC has encountered [[Reductionist|reductionists]] who see [[complexity]] as an [[emergent]] property of even a simple [[algorithm]] of Turing Machine. | ||
On this view, even something as simple as [[Conway’s Game of Life]] is, if you let it go long enough, [[complex]], as it spawns sub-systems, gliders, glider guns, and these interact with each other in marvellous and unpredictable ways. There is a tacit assumption here that real life — you know, the [[offworld]] — is really just a scaled-up version of the Game of Life, itself being just an implementation of {{br|Darwin’s Dangerous Idea}}, after all. | On this view, [[fractal]]s, [https://en.wikipedia.org/wiki/Logistic_map polynomial mapping], even something as simple as [[Conway’s Game of Life]] is, if you let it go long enough, [[complex]], as it spawns sub-systems, gliders, glider guns, and these interact with each other in marvellous and unpredictable ways. There is a tacit assumption here that real life — you know, the [[offworld]] — is really just a scaled-up version of the Game of Life, itself being just an implementation of {{br|Darwin’s Dangerous Idea}}, after all. | ||
This is [[reductionism]], only viewed from the wrong end of the telescope. Rather than taking the rich tapestry of modern life and boiling it down to basic rules of cause and effect, as [[reductionist|reductionists]] normally do, this gambit starts with those basic rules, and scales them up. What prevents us from getting from one end of this spectrum to the other, say the reductionists, is only an absence of sufficient [[data]] to reverse engineer the algorithm (from the rich tapestry end) and a want of processing power to generate modern life (from the basic algorithm end). The universe is nonetheless fully determined at all levels of abstraction. | This is [[reductionism]], only viewed from the wrong end of the telescope. Rather than taking the rich tapestry of modern life and boiling it down to basic rules of cause and effect, as [[reductionist|reductionists]] normally do, this gambit starts with those basic rules, and scales them up. What prevents us from getting from one end of this spectrum to the other, say the reductionists, is only an absence of sufficient [[data]] to reverse engineer the algorithm (from the rich tapestry end) and a want of processing power to generate modern life (from the basic algorithm end). The universe is nonetheless fully determined at all levels of abstraction. | ||
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Hmm. So however long you run Conway’s life game, it does not seem to arrive at [[rice pudding and income tax]]. Reductionists say “Ah, but that is just because the rules aren’t quite right, or we haven’t quite got the right initial configuration”. But then, they would say that. | Hmm. So however long you run Conway’s life game, it does not seem to arrive at [[rice pudding and income tax]]. Reductionists say “Ah, but that is just because the rules aren’t quite right, or we haven’t quite got the right initial configuration”. But then, they would say that. | ||
==== | ====Complexity as an emergent property of algorithm?==== | ||
The idea that [[complexity]] is merely an [[emergent]] probability of a simple [[algorithm]] is quite the piece of eliminative [[reductionism]]. ''Eliminative'' in that it eliminates complexity as discrete state. It converts all [[complex]] systems to no more than insufficiently-mapped, not-yet-properly-understood [[simple system]]s. | The idea that [[complexity]] is merely an [[emergent]] probability of a simple [[algorithm]] is quite the piece of eliminative [[reductionism]]. ''Eliminative'' in that it eliminates complexity as discrete state. It converts all [[complex]] systems to no more than insufficiently-mapped, not-yet-properly-understood [[simple system]]s. | ||
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In both cases, complex systems present us with unpredictable, non-linear outcomes in edge cases. All that differs is ''why'' they appear that way. (One is “because they are”, the other “because we have no way to better calculate them”. | In both cases, complex systems present us with unpredictable, non-linear outcomes in edge cases. All that differs is ''why'' they appear that way. (One is “because they are”, the other “because we have no way to better calculate them”. | ||
But in the first case, any heuristic that helps us make sense of the system ISAs good as any other. There is no “[[epistemic priority]]” between competing heuristics: all that matters is what works best, judged by whatever criteria you happen to bring to the table. Beauty is in the eye of the beholder. In the other, there ''is'' such an epistemic priority. The most granular binary code is the closest to the truth. This gives the holders of that view grounds for insisting it is preferred, by everyone, over every other heuristic. | But in the first case, any heuristic that helps us make sense of the system ISAs good as any other. There is no “[[epistemic priority]]” between competing heuristics: all that matters is what works best, judged by whatever criteria you happen to bring to the table. Beauty is in the eye of the beholder. In the other, there ''is'' such an [[epistemic priority]]. The most granular binary code is the closest to the truth. This gives the holders of that view grounds for insisting it is preferred, by everyone, over every other heuristic. | ||
====If algorithms are complex, everything is complex — or nothing is==== | ====If algorithms are complex, ''everything'' is complex — or ''nothing'' is==== | ||
Conflating simple algorithms with complex systems undermines the explanatory power of complexity theory. The distinction between [[simple]], [[Complicated system|complicated]] and [[Complex system|complex]] systems is meaningful. They are now just points along a continuum, without hard boundaries between them. It is really just saying, “well, in this complex system, ''something'' will happen; we don’t know what, but as and when it does we will be able to rationalise it as a function of our rules, by deducing what the missing data must have been.” | Conflating simple algorithms with complex systems undermines the explanatory power of complexity theory. The distinction between [[simple]], [[Complicated system|complicated]] and [[Complex system|complex]] systems is meaningful. They are now just points along a continuum, without hard boundaries between them. It is really just saying, “well, in this complex system, ''something'' will happen; we don’t know what, but as and when it does we will be able to rationalise it as a function of our rules, by deducing what the missing data must have been.” | ||
Ex-post facto rationalisation to comply with your rules is rather like the work normal scientists do in a research programme, of course. It is a form of narratisation. | Ex-post facto rationalisation to comply with your rules is rather like the work normal scientists do in a research programme, of course. It is a form of narratisation. | ||