gwern comments on Rationality Quotes September 2011 - Less Wrong
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It's a nice list, but I think the core point strikes me as liable to be simply false. I forget who it was presenting this evidence - it might even have been James Miller, it was someone at the Winter Intelligence conference at FHI - but they looked at (1) the economic gains to countries with higher average IQ, (2) the average gains to individuals with higher IQ, and concluded that (3) people with high IQ create vast amounts of positive externality, much more than they capture as individuals, probably mostly in the form of countries with less stupid economic policies.
Maybe if we're literally talking about a pure speed and LTM pill that doesn't affect at all, say, capacity to keep things in short-term memory or the ability to maintain complex abstractions in working memory, i.e., a literal speed and disk space pill rather than an IQ pill.
Sounds plausible. If anybody finds the citation for this, please post it.
Here's another one: "National IQ and National Productivity: The Hive Mind Across Asia", Jones 2011
"Salt Iodization and the Enfranchisement of the American Worker", Adhvaryu et al 2013:
If, in the 1920s, 10 IQ points could increase your labor participation rate by 1%, then what on earth does the multiplier look like now? The 1920s weren't really known for their demands on intelligence, after all.
And note the relevance to discussions of technological unemployment: since the gains are concentrated in the low end (think 80s, 90s) due to the threshold nature of iodine & IQ, this employment increase means that already, a century ago, people in the low-end range were having trouble being employed.
"Exponential correlation of IQ and the wealth of nations", Dickerson 2006:
It peeves me when scatterplots of GDP per capita versus something else use a linear scale -- do they actually think the difference between $30k and $20k is anywhere near as important as that between $11k and $1k? And yet hardly anybody uses logarithmic scales.
Likewise, the fit looks a lot less scary if you write it as ln(GDP) = A + B*IQ.
Yes, Dickerson does point out that his exponential fit is a linear relationship on a log scale. For example, he does show a log-scale in figure 3 (pg3), fitting the most reliable 83 nation-points on a plot of log(GDP) against mean IQ in which the exponential fit looks exactly like you would expect. (Is it per capita? As far as I can tell, he always means per capita GDP even if he writes just 'GDP'.) Figure 4 does the same thing but expands the dataset to 185 nations. The latter plot should probably be ignored given that the expansion comes from basically guessing:
Is it easy to compare the fit of their theory to the smart fraction theory?
I dunno. I've given it a try and while it's easy enough to reproduce the exponential fit (and the generated regression line does fit the 81 nations very nicely), I think I screwed up somehow reproducing the smart fraction equation because the regression looks weird and trying out the smart-fraction function (using his specified constants) on specific IQs I don't get the same results as in La Griffe's table. And I can't figure out what I'm doing wrong, my function looks like it's doing the same thing as his. So I give up. Here is my code if you want to try to fix it:
(In retrospect, I'm not sure it's even meaningful to try to fit the
sffunction with the constants already baked in, but since I apparently didn't write it right, it doesn't matter.Hm, one thing I notice is that you look like you're fitting sf against log(gdp). I managed to replicate his results in octave, and got a meaningful result plotting smart fraction against gdp.
My guess at how to change your code (noting that I don't know R):
That should give you some measure of how good it fits, and you might be able to loop it to see how well the smart fraction does with various thresholds.
(I also probably should have linked to the refinement.)
I can't tell whether that works since you're just using the same broken smart-fraction
sfpredictor; eg.sf(107,108)~> 32818, while the first smart fraction page's table gives a Hong Kong regression line of 19817 which is very different from 33k.The refinement doesn't help with my problem, no.
Hmmm. I agree that it doesn't match. What if by 'regression line' he means the regression line put through the sf-gdp data?
That is, you should be able to calculate sf as a fraction with
And then regress that against gdp, which will give you the various coefficients, and a much more sensible graph. (You can compare those to the SFs he calculates in the refinement, but those are with verbal IQ, which might require finding that dataset / trusting his, and have a separate IQ0.)
Comparing the two graphs, I find it interesting that the eight outliers Griffe mentions (Qatar, South Africa, Barbados, China, and then the NE Asian countries) are much more noticeable on the SF graph than the log(GDP) graph, and that the log(GDP) graph compresses the variation of the high-income countries, and gets most of its variation from the low-income countries; the situation is reversed in the SF graph. Since both our IQ and GDP estimates are better in high-income countries, that seems like a desirable property to have.
With outliers included, I'm getting R=.79 for SF and R=.74 for log(gdp). (I think, I'm not sure I'm calculating those correctly.)
Trying to rederive the constants doesn't help me, which is starting to make me wonder if he's really using the table he provided or misstated an equation or something:
If you double 34779 you get very close to his $69,321 so there might be something going wrong due to the 1/2 that appears in uses of the
erfto make a cumulative distribution function, but I don't how a threshold of 99.64 IQ is even close to his 108!(The weird start values were found via trial-and-error in trying to avoid R's 'singular gradient error'; it doesn't appear to make a difference if you start with, say,
f=90.)Above link is dead. Here is a new one
http://mason.gmu.edu/~gjonesb/JonesADR
A 2012 Jones followup: "Will the intelligent inherit the earth? IQ and time preference in the global economy"