Averagarianism: Difference between revisions

From The Jolly Contrarian
Jump to navigation Jump to search
No edit summary
No edit summary
 
(15 intermediate revisions by the same user not shown)
Line 1: Line 1:
{{a|devil|}}{{author|Rory Sutherland}} has an excellent [https://youtu.be/UirCaM5kg9E snippet about the danger of managing toward averages]. Among his reasons:
{{a|devil|}}{{dpn|/ˈævᵊrɪʤeəriənɪzᵊm/|n}}The mistake of attributing an emergent mathematical property of a group to some or all the individual members of the group.  
*The average — the top of the bell curve— is where everyone will be targeting their product, so existing markets will be mature, barriers to entry high, and margins will be the slimmest. Go for the tails, find the influencers and meet them drive your product into the mainstream. Have the average follow you, not the other way around.


*Convergence on the same place everyone is converging isn’t good business, but a recipe for ''bankruptcy''. It is a race to the bottom. As with [[evolution]], the secret is to realise the process is a continuous drift ''from'' the unsatisfactory status quo to something else that doesn’t have that drawback, as opposed to a process converging on a consensus. The ecosystem is ''not'' seeking an equilibrium. It is perpetually seeking to ''escape'' it.  
The folly of reasoning from the general to the particular with statistics.


=== Data modernism and the cult of the aggregate ===
For example, the [[Bill Gates on a bus]] paradox: the  ''average'' wealth of 99 bankrupts and one billionaire is ten million dollars. But not one individual in the group has an income anywhere close to ten million dollars. The median wealth is zero. The median effectively discounts outliers either side, so is more likely to represent the “real consensus”.
A prelude to the [[great delamination]]: There is a strand of [[High modernism|modernist]] thinking that flows from Robert Moses, Le Corbusier, that there is an optimisable configuration for human interaction and it can be derived from a rigorously scientific, or at least mathematical, method: that the only obstacle to implementing it has been the lack of a sufficiently powerful machine to run the calculation.


That time has now arrived, or is close at hand, whereby the means is at our disposal. We now have the processing power to take massive amounts of [[unstructured data]] — “[[noise]]in the vernacular —  and from it extrapolate a [[Signal-to-noise ratio|signal]]. We don’t necessarily understand ''how'' the [[algorithm]]<nowiki/>s extrapolate a signal; they just do — this inscrutability  is part of the appeal of it: there is no “all-too-human” bias<ref>At least, until the algo goes rogue and becomes a Nazi.</ref> — but there is a belief which stretches from paid-up Randian anarcho-capitalists through to certified latter-day socialists, that ''we can solve our problems with data''.  
See also the “average fighter pilot,” that Gladwellian character from any number of popular science books.


Now data, as it comes, is an incoherent, imperfect, meaningless thing. It is the pre-theatre chat;  a “hubbub”: made up of millions of individual communications, conversations and interactions actions, all of which have their own (possibly imperfect) meanings between their participants, but which taken as a whole have no particular meaning at all.  
Lesson one: do not manage from the average to the particular.  


Imagine taking every one of the pre-performance conversations between all the patrons at the Saturday matinee performance of ''Eureka Day'' at The Old Vic<ref>Real-life example, needless to say.</ref> — that meaningless hubbub — and summarising it into a single sentence, designed to reflect what “the theatre was thinking”. ''Then'' you feed that  single confabulated sentence back to all the theatre patrons and say “this is the conversation which the theatre was having. Now, which side were you on?” People will tend to take sides, and will invest themselves in that conversation.
Then there is the story — oft repeated at a microscale, ''sans doubte'' — of the global investment bank which addressed its gender pay gap by laterally recruiting a new [[general counsel]] for ten million dollars. Remaining victims of pay disparity remained unmoved, and undercompensated. (This is not to say, “don’t act to correct pay unfairness”; just “don’t do it by massaging the average”. Seek out and rectify, you know, ''actual pay unfairness''. In the particular.)


But, remember, the hubbub was just noise all along. None of the individual conversations had anything to do with each other. All had their own, independent meanings. They are ''immune'' to aggregation.
Lesson two: ''definitely'' do not manage from the particular to the average.


We say “we have unconscious biases and they inform our reactions”. Well, no ''shit''.
===Other reasons not to manage to the average===
{{author|Rory Sutherland}} has an excellent [https://youtu.be/UirCaM5kg9E snippet about the danger of managing toward averages]. Among his reasons:


To extract signal from noise is to filter, limit compress and selectively amplify on the predication that there ''is'' a signal; that that hubbub is something like a de-tuned radio, or we are looking for pulsars, quasars and intelligent life on the SETI array. But we are not. There isn’t always a signal. the SETI array is a bad [[metaphor]]: here we are trying to tease out a bilateral signal that ''is'' there from a spectrum of other kinds of radiation that qualitatively different, but just broadcast on the same frequency. With the human hubbub there are a spectrum of unconnected communications and ''no'' real “signal”. We are not trying to isolate a single conversation out of all the other ones — that is the direct analogy — but trying to extract a an aggregated message that is not actually there, and to treat is as an [[Emergence|emergent]] property of all those conversations. This is a different thing entirely. ''There is no emergent property from millions of  unrelated conversations''. The result is brown, warm and even: maximum ''entropy''.
====Find a niche====
The “average” is where everyone else will target their product. The markets will be mature, barriers to entry high, demand inelastic and margins slim.  


To make something out of nothing is to ''deliberately'' bias.  It is to carve David out of a marble block. Bias ''creates'' meaning. There may be ''local'' meanings — maybe — based on local interactions and echo chambers but these are informal, incomplete, and impossible to delimit.
Go instead for the tails: have the average follow you, not the other way around.  


So we tend to “extrapolate” central figures from random noise: economic growth. The intention behind expressed electoral preference. Average wages. The wage gap. Why the stock market went up. ''That'' the stock market went up: these are spectral figures. They are ghosts, gods, monsters and devils. They are no more real than religions, just because they are the product of “science” and “techne”.
To use a skiing metaphor, the best entertainment to be had is not on the groomed blue motorway with the poseurs, learners, and homicidal teenagers, but [[off piste]]. You just have to know how to ski. So, learn, or take up another hobby.


We have, on occasion, some convenient proxies, but they are just proxies: for example, in an election, a manifesto. Without a manifesto, a binary vote for a single candidate in a local electorate (I am assuming FPP, but in honesty it isn’t wildly different for proportional represerntation) tells us nothing whatever about the individual motivation to vote as she did. A manifesto helps, by a process of [[Deemery|deem]]<nowiki/>ery.  
====Don’t race to the bottom====
Convergence on the same place everyone is converging isn’t good business, but a recipe for ''bankruptcy''. It is a race to the bottom. As with [[evolution]], the secret is to realise the process is a continuous drift ''from'' the unsatisfactory status quo to something else that doesn’t have that drawback, as opposed to a process converging on a consensus. The ecosystem is ''not'' seeking an equilibrium. It is perpetually seeking to ''escape'' it.  


Did every Conservative voter read the party’s manifesto? Almost certainly, no. Did every Conservative voter who did read it subscribe to every line? Again, almost certainly no. Did ''anyone'' subscribe to every line in it? Perhaps, but by no means certainly.  So, can we legitimately infer uniform support for the Conservatives’ manifesto from all who voted Conservative? ''No''. We only do by dint of the political convention that those who vote for a party are deemed to support a manifesto (if one is published). But even that convention is a spectre. And where your vote is an issue-based referendum, there is not even a manifesto. Who knows why 33 million people voted for Brexit? Who could possibly presume to aggregate all those individual value judgments into a single guiding principle? There were 33 million reasons for voting leave. They tell us nothing except... ''leave''.
===Averagarianism===


But yet we draw battle lines and attack based on our own, invented, signals. Trans activists fight for the rights of — and here, I confess immediately, I am doing ''exactly'' what I complain of — exotic, beautiful, fragile, elfen, teen-age dolphin-like creatures of  beguiling androgyny and harmlessness, as if all trans-identifying people are like that. On the other hand, gender-critical activists fight against middle-aged male sex-offenders operating under cover, as if all trans people are like that.
Averagarianism that forces actually different people into generic categories. It imputes commonalities that don’t really exist. Sanding off contours and wonky borders to make everything regular simply because that suits the hyper-scaled prerogatives of commerce.  


Yet such a patently ludicrous argument animates the public square. This is no more real than vampires fighting werewolves. Why do we take it anymore seriously.


Hence the delamination: the online world is a world of extruded ghoulish signals aggregated from the unfiltered noise of discourse. The offline world — can we call it the offworld? — is a world of bilateral conversations, one on one. A world of shades, nuance, detail, richness, complexity's and — for the most part — civility.
{{sa}}
 
*{{br|The End of Average: How to Succeed in a World That Values Sameness}}
 
*[[Metis]]
Feedback loopsand feeding that signal back into the memeplex, without necessarily surveilling it or taking anything out of it.
So it would include machine learning, AI, etc{{sa}}
*[[Big data]]
*[[Big data]]
*[[Data modernism]]
*[[Correlation]]
*[[Correlation]]
*[[Parable of the squirrels]]
*[[Parable of the squirrels]]
{{Ref}}

Latest revision as of 10:49, 15 November 2023


In which the curmudgeonly old sod puts the world to rights.
Index — Click ᐅ to expand:

Comments? Questions? Suggestions? Requests? Insults? We’d love to 📧 hear from you.
Sign up for our newsletter.

Averagarianism
/ˈævᵊrɪʤeəriənɪzᵊm/ (n.)
The mistake of attributing an emergent mathematical property of a group to some or all the individual members of the group.

The folly of reasoning from the general to the particular with statistics.

For example, the Bill Gates on a bus paradox: the average wealth of 99 bankrupts and one billionaire is ten million dollars. But not one individual in the group has an income anywhere close to ten million dollars. The median wealth is zero. The median effectively discounts outliers either side, so is more likely to represent the “real consensus”.

See also the “average fighter pilot,” that Gladwellian character from any number of popular science books.

Lesson one: do not manage from the average to the particular.

Then there is the story — oft repeated at a microscale, sans doubte — of the global investment bank which addressed its gender pay gap by laterally recruiting a new general counsel for ten million dollars. Remaining victims of pay disparity remained unmoved, and undercompensated. (This is not to say, “don’t act to correct pay unfairness”; just “don’t do it by massaging the average”. Seek out and rectify, you know, actual pay unfairness. In the particular.)

Lesson two: definitely do not manage from the particular to the average.

Other reasons not to manage to the average

Rory Sutherland has an excellent snippet about the danger of managing toward averages. Among his reasons:

Find a niche

The “average” is where everyone else will target their product. The markets will be mature, barriers to entry high, demand inelastic and margins slim.

Go instead for the tails: have the average follow you, not the other way around.

To use a skiing metaphor, the best entertainment to be had is not on the groomed blue motorway with the poseurs, learners, and homicidal teenagers, but off piste. You just have to know how to ski. So, learn, or take up another hobby.

Don’t race to the bottom

Convergence on the same place everyone is converging isn’t good business, but a recipe for bankruptcy. It is a race to the bottom. As with evolution, the secret is to realise the process is a continuous drift from the unsatisfactory status quo to something else that doesn’t have that drawback, as opposed to a process converging on a consensus. The ecosystem is not seeking an equilibrium. It is perpetually seeking to escape it.

Averagarianism

Averagarianism that forces actually different people into generic categories. It imputes commonalities that don’t really exist. Sanding off contours and wonky borders to make everything regular simply because that suits the hyper-scaled prerogatives of commerce.


See also

References