0) We don’t have IQ tests from 1830 (the beginning of the revolution). Only response tests from later in the 1800’s. 1) the response tests have dropped. (I am still fussing about this one), and response time is pretty much a proxy for iq (which in an age of neural networks we should understand is obvious). 2) The flynn effect has stopped and now reversed. 3) All the gains were at the bottom of the distribution, and the top has remained the same or decreased. (age confirms it) 4) The differences are not in g-loaded parts of the tests, and g-loaded parts are unchanged. 5) Relative positioning remains constant: —“While the secular gains are on g-loaded tests (such as the Wechsler), they are negatively correlated with the most g-loaded components of those tests. Also, the tests lose their g loadedness over time with training, retesting, and familiarity. In an analysis of mathematics and reading scores from tests such as the NAEP and Coleman Report over the last 54 years, we show that there has been no narrowing of the gap in either IQ scores or in educational achievement. From 1954 to 2008, Black 17-year-olds have consistently scored at about the level of White 14-year-olds, yielding IQ equivale”—- 6) We do in fact get a bit better with practice. Not a lot better but better enough to reduce volatility, which would not improve test coverage, but reduce error in tests performed. In other words we aren’t smarter we reduce errors. 7) General knowledge ‘saturation’ produces patterns involuntarily that has to be learned intentionally (or by reading) as in the past. HOWERVER As I understand it, people are ‘smarter in general’ for the simple reason that by ‘thinking scientifically’ we in fact are training ourselves to apply general rules. In other words, people at the turn of the century were more likely to think in instance-rules and commands, than general rules, and we have in fact gotten better at the use of general rules. Hence why I am an advocate for the German and English Languages, and in particular operational language, because I am certain that the same gains will be produced as were produced by scientific thought (general rules). Ergo, this is much scarier: that means some ideas not only make us dumber, they imprison us in dumbness. MORE LATER.
Theme: Measurement
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The Flynn Effect Explained
0) We don’t have IQ tests from 1830 (the beginning of the revolution). Only response tests from later in the 1800’s. 1) the response tests have dropped. (I am still fussing about this one), and response time is pretty much a proxy for iq (which in an age of neural networks we should understand is obvious). 2) The flynn effect has stopped and now reversed. 3) All the gains were at the bottom of the distribution, and the top has remained the same or decreased. (age confirms it) 4) The differences are not in g-loaded parts of the tests, and g-loaded parts are unchanged. 5) Relative positioning remains constant: —“While the secular gains are on g-loaded tests (such as the Wechsler), they are negatively correlated with the most g-loaded components of those tests. Also, the tests lose their g loadedness over time with training, retesting, and familiarity. In an analysis of mathematics and reading scores from tests such as the NAEP and Coleman Report over the last 54 years, we show that there has been no narrowing of the gap in either IQ scores or in educational achievement. From 1954 to 2008, Black 17-year-olds have consistently scored at about the level of White 14-year-olds, yielding IQ equivale”—- 6) We do in fact get a bit better with practice. Not a lot better but better enough to reduce volatility, which would not improve test coverage, but reduce error in tests performed. In other words we aren’t smarter we reduce errors. 7) General knowledge ‘saturation’ produces patterns involuntarily that has to be learned intentionally (or by reading) as in the past. HOWERVER As I understand it, people are ‘smarter in general’ for the simple reason that by ‘thinking scientifically’ we in fact are training ourselves to apply general rules. In other words, people at the turn of the century were more likely to think in instance-rules and commands, than general rules, and we have in fact gotten better at the use of general rules. Hence why I am an advocate for the German and English Languages, and in particular operational language, because I am certain that the same gains will be produced as were produced by scientific thought (general rules). Ergo, this is much scarier: that means some ideas not only make us dumber, they imprison us in dumbness. MORE LATER.
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Economics of Neural Networks
Any “general rule of arbitrary precision” must include a limit (time delineation) in order to categorize and test an outcome(consequence), since we may categorize consequences at any point in the time line in which actionable or deducible constant relations are identifiable. In other words, searches for prediction of futures are change (state) dependent. This may be heavy but it means that your prediction of future events from any state may vary by the utility you prefer. We must operate by general rules (categories) because that is all we can act upon (a concentration of constant relations during which we can effect a change in state.) We all bias our utility (judgements) on similar timelines if not only due to ability, but also on commensurability. Ergo, we develop out of necessity time preferences and the more expertise we develop in any time frame the more related (dependent) associations we develop in concert. This isn’t just choice it’s the economics of neural networks, and that economics is no different from the ‘economics’ of physics, biology, and sentience. (for Andy Curzon) Apr 18, 2018 9:59am
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Economics of Neural Networks
Any “general rule of arbitrary precision” must include a limit (time delineation) in order to categorize and test an outcome(consequence), since we may categorize consequences at any point in the time line in which actionable or deducible constant relations are identifiable. In other words, searches for prediction of futures are change (state) dependent. This may be heavy but it means that your prediction of future events from any state may vary by the utility you prefer. We must operate by general rules (categories) because that is all we can act upon (a concentration of constant relations during which we can effect a change in state.) We all bias our utility (judgements) on similar timelines if not only due to ability, but also on commensurability. Ergo, we develop out of necessity time preferences and the more expertise we develop in any time frame the more related (dependent) associations we develop in concert. This isn’t just choice it’s the economics of neural networks, and that economics is no different from the ‘economics’ of physics, biology, and sentience. (for Andy Curzon) Apr 18, 2018 9:59am
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Language and Abilities
***Languages evolve to suit the ‘computational’ abilities of the demographics that they serve. And they further evolve to to suit the technical, economic, and political complexity that they serve. In most cases, the difference between languages has to do with the demands of their state of development.*** (Worth Repeating)
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Language and Abilities
***Languages evolve to suit the ‘computational’ abilities of the demographics that they serve. And they further evolve to to suit the technical, economic, and political complexity that they serve. In most cases, the difference between languages has to do with the demands of their state of development.*** (Worth Repeating)
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***Languages evolve to suit the ‘computational’ abilities of the demographics th
***Languages evolve to suit the ‘computational’ abilities of the demographics that they serve. And they further evolve to to suit the technical, economic, and political complexity that they serve. In most cases, the difference between languages has to do with the demands of their state of development.***
(Worth Repeating)
Source date (UTC): 2018-04-18 13:46:00 UTC
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CREATING NEW UNDERSTANDING IS VERY HARD, DISCIPLINED, TIME CONSUMING WORK. It ta
CREATING NEW UNDERSTANDING IS VERY HARD, DISCIPLINED, TIME CONSUMING WORK.
It takes an extraordinary long time to simplify a very complex set of ideas into a language consisting of a sufficiently small set of general rules, that they can be taught within the ability, patience, and incentives available to the audience.
(this shit I do is f’king hard, which is why it takes so long. I have become much much better at communicating these ideas over time, and that’s because I work, much, much, harder with more discipline with lower tolerance for error, than anyone else I have know, and the only other person I really can commiserate with is Kant – and he was wrong – even if I identify with Hayek [information] in nearly everything. Hume and Smith were innovative and insightful but they lacked legal rigour. As far as I know it takes nine to ten years of research on an innovation to develop marginally indifferent ability in any discipline. I knew that going in. And I knew I was slower that most. But sometimes I wake up from my work and look back and realize that no sane person would do this kind of thing without a cognitive bias to work endlessly [hyper orderliness], and in pursuit of a solution to a problem [threat] that’s pervasive [cultural or civilizational]. )
Source date (UTC): 2018-04-18 10:09:00 UTC
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Any “general rule of arbitrary precision” must include a limit (time delineation
Any “general rule of arbitrary precision” must include a limit (time delineation) in order to categorize and test an outcome(consequence), since we may categorize consequences at any point in the time line in which actionable or deducible constant relations are identifiable. In other words, searches for prediction of futures are change (state) dependent.
This may be heavy but it means that your prediction of future events from any state may vary by the utility you prefer.
We must operate by general rules (categories) because that is all we can act upon (a concentration of constant relations during which we can effect a change in state.)
We all bias our utility (judgements) on similar timelines if not only due to ability, but also on commensurability. Ergo, we develop out of necessity time preferences and the more expertise we develop in any time frame the more related (dependent) associations we develop in concert.
This isn’t just choice it’s the economics of neural networks, and that economics is no different from the ‘economics’ of physics, biology, and sentience.
(for Andy Curzon)
Source date (UTC): 2018-04-18 09:59:00 UTC
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THE FLYNN EFFECT EXPLAINED 0) We don’t have IQ tests from 1830 (the beginning of
THE FLYNN EFFECT EXPLAINED
0) We don’t have IQ tests from 1830 (the beginning of the revolution). Only response tests from later in the 1800’s.
1) the response tests have dropped. (I am still fussing about this one), and response time is pretty much a proxy for iq (which in an age of neural networks we should understand is obvious).
2) The flynn effect has stopped and now reversed.
3) All the gains were at the bottom of the distribution, and the top has remained the same or decreased. (age confirms it)
4) The differences are not in g-loaded parts of the tests, and g-loaded parts are unchanged.
5) Relative positioning remains constant:
—“While the secular gains are on g-loaded tests (such as the Wechsler), they are negatively correlated with the most g-loaded components of those tests. Also, the tests lose their g loadedness over time with training, retesting, and familiarity. In an analysis of mathematics and reading scores from tests such as the NAEP and Coleman Report over the last 54 years, we show that there has been no narrowing of the gap in either IQ scores or in educational achievement. From 1954 to 2008, Black 17-year-olds have consistently scored at about the level of White 14-year-olds, yielding IQ equivale”—-
6) We do in fact get a bit better with practice. Not a lot better but better enough to reduce volatility, which would not improve test coverage, but reduce error in tests performed. In other words we aren’t smarter we reduce errors.
7) General knowledge ‘saturation’ produces patterns involuntarily that has to be learned intentionally (or by reading) as in the past.
HOWERVER
As I understand it, people are ‘smarter in general’ for the simple reason that by ‘thinking scientifically’ we in fact are training ourselves to apply general rules. In other words, people at the turn of the century were more likely to think in instance-rules and commands, than general rules, and we have in fact gotten better at the use of general rules. Hence why I am an advocate for the German and English Languages, and in particular operational language, because I am certain that the same gains will be produced as were produced by scientific thought (general rules).
Ergo, this is much scarier: that means some ideas not only make us dumber, they imprison us in dumbness.
MORE LATER.
Source date (UTC): 2018-04-17 23:01:00 UTC