Speak of the intellectual life and a lot of people will think you’re pretentious; they think you’re calling yourself intelligent.
What they don’t understand is that the intellectual is a type of person who can be found across the intelligence distribution. The defining characteristic of the intellectual is an irrepressible lust for the truth. The technical concept from the psychology literature is need for cognition. Intelligence is only weakly correlated with need for cognition (probably somewhere between .14 and .28).
It’s likely that popular conspiracy theories are authored and promoted by people with high need for cognition. If you look closely at the Flat Earth community, for instance, many of the active members devote a lot of time and energy to effortful research, even to the point of conducting relatively serious field experiments.
The number of genuine intellectuals is higher than people realize. The number of highly intelligent pseudo-intellectuals is also higher than people realize.
If you want to disrupt the Higher Education industry—whether you’re a thinker, creator, or entrepreneur—this might be one of the most important and best-kept secrets.
Decouple intellectualism and intelligence. You’ll be surprised what you find.
Intelligence is increasingly a political cleavage, thanks to the phenomenon of skill-biased technological change.
If your income is earned through competition on an open market, intelligence is an unambiguous good. You need it, you want it, possessing it makes you succeed and lacking it makes you fail. The continued development and maximization of artificial intelligence is an obvious and mundane reality of business development.
If your income is earned through a bureaucratic office of any kind, success in that office increasingly requires opposition to intelligence as such. Unions were always essentially anti-intelligence structures, defending humans from innovative insights that threatened to displace them. But unions were defeated by the information revolution, which was a kind of global unleashing of distributed intelligence. Now, atomized individuals within bureaucratic structures spontaneously converge on anti-intelligence strategies, in a shared sub-conscious realization that their income and status will not survive any further rationalization.
How else do you explain the recent co-occurrence of the following?
Mass political opposition to mundane psychology research on intelligence
Evangelical public moralizing against competence as an increasingly visible career track (in journalism, some academic disciplines, the non-profit sector, etc.)
Social justice culture in general as a kind of diffuse “cognitive tax.” It is a distributed campaign to decrease the returns to thinking while increasing the returns to arbitrary dicta.
The popularity of pseudoscientific concepts serving as supposed alternatives to intelligence, e.g. “emotional intelligence,” “learning styles,” etc.
Finally, it is no surprise that many of these symptoms are rooted in academia. This is predicted by the theory. The authority and legitimacy of the Professor is predicated on their superior intelligence, and yet their income and status is predicated on anti-intelligent cartel structures (like all bureaucratic professions). It is no wonder, then, that increasing intelligence pressures are short-circuiting academic contexts first and foremost.
Once upon a time, professors could enjoy the privilege of merely slacking on competitive intelligence application. These were the good old days, before digitalization. Professors could be slackers and eccentrics: a low-level and benign form of anti-intelligenic intellectualism. They didn’t have to actively attack and mitigate intelligence as such. Today, given the advancement of digital economic rationalization, humanities professors work around the clock to stave off ever-encroaching intelligence threats.
The difficult irony is that anti-intelligence humanity professors are acting intelligently. It is perfectly rational for them to play the game they are playing. Not unlike CEOs, they are applying their cognition to maximize the profit of the ship they are stuck on.
In a recent post, I encountered an interesting empirical fact about the college wage premium accruing to low-ability college grads over the period 1979-1994. Looking at a 2003 article by Tobias, I wrote: "There is a lot of temporal volatility for the class of low-ability individuals. In fact, for low-ability individuals there is not even a consistent wage premium enjoyed by the college-educated until 1990."
I have begun to wonder if this pattern has anything to do with the non-linear relationship between GPA and PC. If the low-ability college entrants feel they are much less certain to enjoy a wage premium over the "townie losers" they left behind, what better strategy than to invest their college-specific word games with extreme moral significance? That way, even the dumbest college grad can be confident that they will remaindistinguished from the more able among the non-college-grads.
[Hat tip to a few high-quality comments on this blog recently, I don't recall exactly but I think someone may have made a point similar to this; the seed of this post might have been planted there, thank you.]
Although this last point is only conjecture, it is curious that right when the wage premium for low-ability college grads arrives is right when the first wave of campus political correctness kicks off — the early 1990s. Especially if you buy Caplan's signaling theory of education, it's not at all implausible that for low-ability college grads their wage-premium is secured primarily through a specialization in moral signaling.
A reader/watcher/listener has brought to my attention another paper, which shows that, for college-educated individuals, earnings are a non-linear function of cognitive ability or g — at least in the National Longitudinal Survey of Youth from 1979-1994. The paper is a 2003 article by Justin Tobias in the Oxford Bulletin of Economics and Statistics.
There may be other studies on this question, but a selling point of this article is that it tries to use the least restrictive assumptions possible. Namely, allowing for non-linearities. In the social sciences, there is a huge bias toward finding linear effects, because most of the workhorse models everyone learns in grad school are linear models. Non-linear models are trickier and harder to interpret and so they're just used much less, even in contexts where non-linearities are very plausible.
A common motif in "accelerationist" social/political theories is the exponential curve. Many of us have priors suggesting that, at least for most of the non-trivial tendenices characterizing modern polities, there are likely to be non-linear processes at work. If the contemporary social scientist using workhorse regression models is biased toward finding linear effects, accelerationists tend to go looking for non-linear processes at the individual, group, nation, or global level. So for those of us who think the accelerationist frame is the one best fit to parsing the politics of modernity, studies allowing for non-linearity can be especially revealing.
The first main finding of Tobias is visually summarized in the figure below. Tobias has more complicated arguments about the relationship between ability, education, and earnings, but we'll ignore those here. Considering college-educated individuals only, the graph below plots on the y-axis the percentage change in wages associated with a one-standard-deviation increase in ability, across a range of abilities. Note that whereas many graphs will show you how some change in X is associated with some change in Y, this plot is different: It shows the marginal effect of X on Y, but for different values of X.
The implication of the above graph is pretty clear. It just means that the earnings gain from any unit increase in g is greater at higher levels of g. An easy way to summarize this is to say that the effect of X on Y is exponential or multiplicative. Note also there's nothing obvious about this effect; contrast this graph to the diminishing marginal utility of money. Gaining $1000 when you're a millionaire has less of an effect on your happiness than if you're at the median wealth level. But when it comes to earnings, gaining a little bit of extra ability when you're already able is worth even more than if you were starting at a low level of ability.
The paper has a lot of nuances, which I'm blithely steamrolling. My last paragraph is only true for the college educated, and there are a few other interesting wrinkles. But this is a blog, and so I mostly collect what is of interest to me personally. Thus I'll skip to the end of the paper, where Tobias estimates separate models for each year. The graph below shows the size of the wage gap between the college-educated and the non-college-educated, for three different ability types, in each year. The solid line is one standard deviation above the mean ability, the solid line with dots is mean ability, and the dotted line is one standard deviation below the mean ability.
An obvious implication is that the wage gap increases over this period, more or less for each ability level. But what's interesting is that the slope looks a bit steeper, and is less volatile, for high-ability than for average and low-ability. There is a lot of temporal volatility for the class of low-ability individuals. In fact, for low-ability individuals there is not even a consistent wage premium enjoyed by the college-educated until 1990.
Anyway, file under runaway intelligence takeoff...
Following on my post from yesterday, I've been thinking about how the widespread and often racist views of "welfare" in the United States — especially among poor whites — fester on top of the educated-progressive party line that heritable IQ differences are bunk.
An interesting wrinkle from the study I cited yesterday (Papageorge and Thom 2018) is that the genetics-earnings link is conditioned by family SES. In other words, children with strong genetic endowments for abstract intelligence will not reach their full earnings potential if they are hampered by a poor family environment.
This is consistent with the left-hereditarian position that the normalization and de-stigmatization of IQ differences and IQ testing would, on net, help poor and stereotyped minorities the most. There are highly gifted children in poor and/or minority communities who are not meeting their potential, and we should do everything we can to support them, including the use of IQ tests to fast-track their selection into new opportunities. One could also argue on this basis that redistributive support for such communities is more necessary and/or more "deserved." I'm not personally interested in gradations of desert as a framing for the ethical necessity of egalitarian arrangements, but others might be.
Some of the anti-welfare and anti-black political sentiment of whites is based on the belief that poor black communities should be written off as hopeless in general. This impression is at least partially due to the fact that a lot of government redistribution over the past few decades has been based on truly naïve and false blank-slate ideology, so people now infer that no amount of redistribution could possibly help poor black communities, if it hasn't yet. They come to think we should stop "throwing good money after bad," when they might well be open to throwing good, smarter money after all the bad, dumb money of past efforts. Understanding the reality of how genetic endowments affect economic outcomes, and how those endowments are distributed, promises more than one way to shake up the whole reactionary, conventional framing of welfare politics in general.
Someone sent me a recent NBER working paper by Nicholas W. Papageorge and Kevin Thom on polygenic scores and educational attainment/earnings. Most pertinent to my theoretical interests is that the link between genes and income appears to increase over recent decades.
In my lectures on the politics of media (really about the politics of technology more generally), I dedicate a session to the topic of skill-biased technical change (SBTC). While the econometrics and specific interpretations are debated, there is a literature in Economics that suggests certain technological innovations (i.e. computing) increase the earnings of the highly skilled relative to the less skilled. I would sometimes wonder to what degree "skills," which sound like primarily acquired things, in fact reflect heritable traits. Or if one could separate these out...
Papageorge and Thom provide one of the first efforts to study this question explicitly. "This is the first study to estimate the returns to genetic factors associated with education using micro genetic data and disaggregated measures of earnings and job tasks across cohorts."
Here is their summary of the genetic effect, conditional on time period:
The returns to these genetic endowments appear to rise over time, coinciding with the rise in income inequality after 1980. Accounting for degree and years of schooling, a one standard deviation increase in the score is associated with a 4.5 percent increase in earnings after 1980. These results are consistent with recent literature on income inequality showing not only an increase in the college premium, but also a rise in the residual wage variance within educational groups (Lemieux, 2006). We also find a positive association between the score and the kinds of non-routine job tasks that benefited from computerization and the development of more advanced information technologies (Autor, Levy, and Murnane, 2003). This provides suggestive evidence that the endowments linked to more educational attainment may allow individuals to either better adapt to new technologies, or specialize in tasks that more strongly complement these new technologies.
Basically, they observe what you would expect to observe if the computerization that begins around 1980 allowed the escape and takeoff of "non-routine analytic" power or abstract intelligence by those most genetically blessed with it. Implicitly, individuals less genetically blessed with "non-routine analytic" powers begin to be left behind around 1980.
Their findings cannot explain the entire postwar dynamic of increasing inequality and relative stagnation of the lower classes, however, because the flatlining of median wages begins around 1973 if I recall correctly. The study seems somewhat coy about naming or even labeling the polygenic score; but my non-expert intuition is that it would have to be something quite akin to what is called the "g-factor" or general intelligence, right?
One limitation of the study is that they use a dummy variable for the period after 1980. I would be curious to see what happens if one re-runs their models with a continuous variable for year. My intuition is that individual-level economic outcomes are more skill-biased/g-loaded today than in the 1980s, but I'm not yet up on any studies this precise on that question in particular.