Signal-to-noise ratio: Difference between revisions
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::{{author|W. E. Deming}} | ::{{author|W. E. Deming}} | ||
At the foot of Deming’s fashionable quote, one can lay a great deal of responsibility for the dogmatic madness our age. | At the foot of Deming’s fashionable quote, one can lay a great deal of responsibility for the dogmatic madness our age. | ||
For if we accept the information content of the universe, through all time and space, is infinite,<ref>This assumes there is not a finite end-point to the Universe; by no means settled, but hardly a rash assumption. And given what we know, the universe’s total information content ''might as well be'' infinite when compared to our finite collection of mortal data.</ref> and the data homo sapiens has collected or generated to the point of reading is finite — this is necessarily so, even if we’ve lost quite a lot of it along the way — then it follows that the total value of [[data]] in which Deming would have us trust is, mathematically, ''as good as nil''. | |||
And that is before considering the quality of the [[data]] we have managed to gather in its own terms. If 90% of all data originates from the internet age,<ref>Eric Schmidt said something like this in 2011, and it sounds [https://blog.rjmetrics.com/2011/02/07/eric-schmidts-5-exabytes-quote-is-a-load-of-crap/ totally made up], but let’s run with it, hey?</ref> so a good portion is cat videos and hot takes on [[Twitter]] — in its own terms. But leave the banality of our age to one side — we don’t need it to make out the argument, and besides, most of those people on Twitter think they are very clever. | |||
In any case, if we transcend our meagre [[hermeneutic]] bubbles, the [[signal-to-noise ratio|signal]] of our data to the noise of all ''possible'' data out there is ''infinitesimal''.<ref>That means, ''really'' small.</ref> | |||
So you might wonder what is so wrong with God. But we humans are [[The Patterning Instinct: A Cultural History of Humanity’s Search for Meaning - Book Review|pattern-seeking machines]]. We don’t take the data as we see it cold, and fashion objective axioms from it, carving nature at its joints: we bring our idiosyncratic prisons and pre-existing cognitive structures to it and willfully create suitable patterns from it to support our convictions. This is not a criticism, but an observation. This is the doom our incarcerate race endures. | |||
It is not just the Twitterati. Science, too, has its [[confirmation bias]], that subsists at a meta-level beyond control by double-blind testing methodologies. Experiments which ''confirm'' a hypothesis are ''a lot'' more likely to be published than those which ''don’t''.<ref>{{br|The Hidden Half: How the World Conceals its Secrets}}, by Michael Blastland.</ref> Of those failed experiments that ''are'' published fewer are cited in other literature. [[Falsification]]s ''die''. | |||
It is | This is neither a cause for alarm nor is it new. It is is a reminder of the importance, in all human discourse, of contingency, provisionality, and above all humility. | ||
All of these are another way of attacking a familiar problem: the world is [[complex]], not merely [[complicated]]. [[Complication]] is a function of a [[paradigm]]. It is part of the game. It is within the rules. It is soluble, by sufficiently skilled application of the rules. Complication can be beaten by an algorithm. You can brute force it. | |||
[[Complexity]], you cannot. | |||
[[Complexity]] | [[Complexity]], describes the ''limits'' of the [[paradigm]]. [[Complexity]] is the wilderness ''beyond'' the [[rules of the game]]. [[Complexity]] inhabits the noise, not the signal. Where there is complexity, ''the rules do not work''. | ||
This is why physical sciences apparently have a greater success than social sciences — cue Richard Dawkins’ obligatory scoff. Physical sciences generally address behaviour of independent events — rolling balls, [[Coin flip|flipping coins]], waves [[and/or]] particles of light. But rolling balls are not autonomous agents. They act independently. The behaviour of one will not influence that of another. Each [[coin flip]] is, as a condition of probability theory — independent.<ref>The technical term: “platykurtic”.</ref> Independent events obey Gaussian principles. They may be modelled. That is to say, they may be [[complicated]] but they remain predictable, at least in theory. When physical systems inexplicably go bang — Chernobyl, the Space Shuttle Challenger, the ''Torrey Canyon'' — the root cause will not be a failure of the physical science underlying the engineering, but some supervening cause invalidating the underlying assumptions on which the physical science was based. | |||
[[Social science]]s don’t have that get-out-of-jail-free card: they address precisely that kind of supervening cause: behaviour that is, intrinsically, ''un''predictable. Psychology, sociology, anthropology, economics — these concern themselves with human agents, who ''are'' influenced by each other — which is why we don’t use physical science to predict their behaviour. Social sciences have to deal with the inherently complex, non-Gaussian interactions between human beings.<ref>physical sciences set up [[hermeneutics|hermeneutic]] systems within which their rules will work, and often these systems are dramatically simplified: Newton, for example, assumes a frictionless, stationery, stable, neutral frame of reference: circumstances which, in any observed environment, do not and ''cannot'' not exist. {{author¬Nancy Cartwright}} calls these structures “[[nomological machine]]s”. Because of this explicit caveat, we can put any variances between Newton’s prediction and the observed outcome down not to [[falsification]], but to the messy real world “contaminating” the idealised experimental conditions. Hence, the proverbial [[crisp packet blowing across St Mark’s Square]].</ref> | |||
{{Sa}} | {{Sa}} | ||
*{{br|The Patterning Instinct: A Cultural History of Humanity’s Search for Meaning}} | |||
*[[nomological machine]] | *[[nomological machine]] | ||
*[[Complexity]] | *[[Complexity]] | ||
*[[Systems theory]] | *[[Systems theory]] | ||
{{ref}} | {{ref}} | ||
Revision as of 13:48, 30 August 2020
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- Caught in a mesh of living veins,
- In cell of padded bone,
- He loneliest is when he pretends
- That he is not alone.
- We’d free the incarcerate race of man
- That such a doom endures
- Could only you unlock my skull,
- Or I creep into yours.
- Ogden Nash, Listen...
- In God we trust, all others must bring data.
At the foot of Deming’s fashionable quote, one can lay a great deal of responsibility for the dogmatic madness our age.
For if we accept the information content of the universe, through all time and space, is infinite,[1] and the data homo sapiens has collected or generated to the point of reading is finite — this is necessarily so, even if we’ve lost quite a lot of it along the way — then it follows that the total value of data in which Deming would have us trust is, mathematically, as good as nil.
And that is before considering the quality of the data we have managed to gather in its own terms. If 90% of all data originates from the internet age,[2] so a good portion is cat videos and hot takes on Twitter — in its own terms. But leave the banality of our age to one side — we don’t need it to make out the argument, and besides, most of those people on Twitter think they are very clever.
In any case, if we transcend our meagre hermeneutic bubbles, the signal of our data to the noise of all possible data out there is infinitesimal.[3]
So you might wonder what is so wrong with God. But we humans are pattern-seeking machines. We don’t take the data as we see it cold, and fashion objective axioms from it, carving nature at its joints: we bring our idiosyncratic prisons and pre-existing cognitive structures to it and willfully create suitable patterns from it to support our convictions. This is not a criticism, but an observation. This is the doom our incarcerate race endures.
It is not just the Twitterati. Science, too, has its confirmation bias, that subsists at a meta-level beyond control by double-blind testing methodologies. Experiments which confirm a hypothesis are a lot more likely to be published than those which don’t.[4] Of those failed experiments that are published fewer are cited in other literature. Falsifications die.
This is neither a cause for alarm nor is it new. It is is a reminder of the importance, in all human discourse, of contingency, provisionality, and above all humility.
All of these are another way of attacking a familiar problem: the world is complex, not merely complicated. Complication is a function of a paradigm. It is part of the game. It is within the rules. It is soluble, by sufficiently skilled application of the rules. Complication can be beaten by an algorithm. You can brute force it.
Complexity, you cannot.
Complexity, describes the limits of the paradigm. Complexity is the wilderness beyond the rules of the game. Complexity inhabits the noise, not the signal. Where there is complexity, the rules do not work.
This is why physical sciences apparently have a greater success than social sciences — cue Richard Dawkins’ obligatory scoff. Physical sciences generally address behaviour of independent events — rolling balls, flipping coins, waves and/or particles of light. But rolling balls are not autonomous agents. They act independently. The behaviour of one will not influence that of another. Each coin flip is, as a condition of probability theory — independent.[5] Independent events obey Gaussian principles. They may be modelled. That is to say, they may be complicated but they remain predictable, at least in theory. When physical systems inexplicably go bang — Chernobyl, the Space Shuttle Challenger, the Torrey Canyon — the root cause will not be a failure of the physical science underlying the engineering, but some supervening cause invalidating the underlying assumptions on which the physical science was based.
Social sciences don’t have that get-out-of-jail-free card: they address precisely that kind of supervening cause: behaviour that is, intrinsically, unpredictable. Psychology, sociology, anthropology, economics — these concern themselves with human agents, who are influenced by each other — which is why we don’t use physical science to predict their behaviour. Social sciences have to deal with the inherently complex, non-Gaussian interactions between human beings.[6]
See also
- The Patterning Instinct: A Cultural History of Humanity’s Search for Meaning
- nomological machine
- Complexity
- Systems theory
References
- ↑ This assumes there is not a finite end-point to the Universe; by no means settled, but hardly a rash assumption. And given what we know, the universe’s total information content might as well be infinite when compared to our finite collection of mortal data.
- ↑ Eric Schmidt said something like this in 2011, and it sounds totally made up, but let’s run with it, hey?
- ↑ That means, really small.
- ↑ The Hidden Half: How the World Conceals its Secrets, by Michael Blastland.
- ↑ The technical term: “platykurtic”.
- ↑ physical sciences set up hermeneutic systems within which their rules will work, and often these systems are dramatically simplified: Newton, for example, assumes a frictionless, stationery, stable, neutral frame of reference: circumstances which, in any observed environment, do not and cannot not exist. Template:Author¬Nancy Cartwright calls these structures “nomological machines”. Because of this explicit caveat, we can put any variances between Newton’s prediction and the observed outcome down not to falsification, but to the messy real world “contaminating” the idealised experimental conditions. Hence, the proverbial crisp packet blowing across St Mark’s Square.