Variation in general intelligence and our evolutionary history

In a bit of “TMI”, I’m far more intellectually promiscuous than I am in my personal life. My primary focus on this blog, if I have one, is probably historical population genetics of the sort highlighted in David Reich’s Who We Are and How We Got Here. But I have plenty of other interests, from economic history to cognitive psychology. Like religion, I have precise and clear opinions about a topic like “intelligence.” Unlike many people with an interest in evolutionary genetics I have read psychometric work, am familiar with some of the empirical results, as well as being personally acquainted with people in the field of psychometrics.

A few days ago Nassim Nicholas Taleb opined on intelligence, and I was silent. Today some individuals who I know from within the field of cultural evolution, another one of my interests, discussed intelligence, and I was silent. I’ve said all I really have to say over 15 years, and it isn’t as if I reanalyze psychometric data sets. But, a question that Taleb acolytes (and presumably Taleb) have brought up is if intelligence is such an important heritable trait, why isn’t everyone much smarter?

Think of this as the second Von Neumann paradox. What I’m alluding to is the fact that we know for a fact that human biology is capable of producing a god-made-flesh. With all due respect to another Jew who lived 2,000 years earlier than him, I speak here of John Von Neumann. We know that he is possible because he was. So why are the likes of Von Neumann bright comets amongst the dust of the stars of the common man, rather than the norm?

First, consider the case of Von Neumann himself. He had one daughter and two grandchildren. That is, within two generations genetically there was less “Von Neumann” than there had been. Though his abilities were clearly mentat-like, from the perspective of evolution Von Neumann was not a many sigma individual. He was within the normal range. Close to the median, a bit below in fecundity and fitness.

Taking a step back and focusing on aggregate populations, the fact that intelligence seems to be a quantitative trait that is at least moderately heritable and normally distributed due to polygenic variation tells us some things evolutionarily already. In Principles of Population Genetics is noted that heritable quantitative traits are often those where directional selection is not occurring due to huge consistent fitness differentials within the population.

Breaking it down, if being very smart was much, much, better than being of average smarts, then everyone would become very smart up to the physiological limit and heritable genetic variation would be removed from the population. Characteristics with huge implications for fitness tend not to be heritable because natural selection quickly expunges the deleterious alleles. The reason that fingerprints are highly heritable is that the variation genetically is not much impacted by natural selection.

The fact that being very intelligent is not evolutionarily clearly “good” seems ridiculousness to many people who think about these things. That’s because if you think about these things, you are probably very good at thinking, and no one wants to think that what they are good at is not evolutionarily very important. The thinking man cannot comprehend that thinking is not the apotheosis of what it is to be a man (similarly, the thinking religious man sometimes confuses theological rumination with the heights of spirituality; reality is that man does not know god through analysis, man experiences god).

So let’s talk about another quantitative trait which is even more heritable than intelligence, and easier to measure: height. In most societies males, in particular, seem to be more attractive to females if they are taller. As a male who is a bit shorter than the American average, it is obvious that there is some penalty to this in social and potentially reproductive contexts. And yet there is normal variation in height, and some populations seem to be genetically smaller than others, such as the Pygmy peoples of the Congo rainforest. Why?

Though being a tall male seems in most circumstances to be better in terms of physical attractiveness than being a short male, circumstances vary, and being too tall increases one’s mortality and morbidity. Being larger is calorically expensive. Large people need to eat more because they have larger muscles. Selection for smaller size in many marginalized rainforest populations is indicative of the fact that in such calorically challenging environments (humans in rainforests have to work hard to obtain enough calories in a hunter-gatherer context), the fitness gain due to intrasexual competition is balanced by reduced fitness during times of ecological stress as well as individual correlated responses (very large males die more often than smaller males).

Additionally, for height I mentioned the sexual component: there does not seem to be a necessary association with higher reproductive fitness with being a tall woman. Though this is subject to taste and fashion, there is likely some antagonistic selection across the two sexes at work, where tall men are the fathers of taller daughters, whose reproductive fitness may actually be lower than smaller women. And vice versa, as short men may produce more fit short daughters (though again, this depends on ecological context and cultural preconditions).

Being very large impacts fitness through the genetic correlation of size with other characteristics. Very large males are subject to higher risk for sudden tears in their lungs, or suboptimal cardiac function. Humans select chickens to be very large in the breast for food, but these chickens can barely walk, and may not be able to reproduce without assistance. Evolution in a quantitative genetic sense may then be all about trade-offs.

So let’s go back to intelligence. What could be the trade-offs? First, there are now results presented at conferences that very high general intelligence may exhibit a correlation with some mental pathologies. Though unpublished, this aligns with some prior intuitions. Additionally, there is the issue where on some characteristics being “species-typical” increases reproductive fitness (an average size nose), while in other characteristics being at an extreme is more attractive (very curvy women with large eyes and small chins; secondary sexual characteristics). Within intelligence, one could argue that being too deviated from the norm might make socialization and pair-bonding difficult. Here is an anecdote about the genius Von Neumann:

Neumann married twice. He married Mariette Kövesi in 1930. When he proposed to her, he was incapable of expressing anything beyond “You and I might be able to have some fun together, seeing as how we both like to drink.”

Apparently having a very fast analytic mind which can engage in abstraction and conceptual manipulation does not mean that one can come up with anything better than that when it came to procuring a mate. And procuring a mate is one of the only “good” things from an evolutionary perspective.

The human mind is neither universally plastic, nor it is a prefabricated set of specialized modules. It is a mix of both. We clearly have some “pre-loaded” code, such as the ability to recognize faces intuitively and rapidly (which a small proportion of the population lacks). But other competencies develop over time, co-opting neurological architecture that grew organically for other purposes. In Reading in the Brain Stanislas Dehaene recounts how the region which specializes in the ability to recognize letter shapes is a preexistent visual-spatial module, probably developed for ecological adaptation to environments where recognition of various organic and inorganic objects was of fitness relevance (obviously now tied in to regions of the brain geared toward verbal comprehension). Dehaene even seems to suggest there may be a trade-off between various cognitive capacities when comparing individuals from urban developed societies and individuals from non-literate small-scale societies.

As human societies have specialized over the last 10,000 years a small number of people who naturally were on the end of a particular distribution in abstraction-and-analysis ability began to preferentially fill exotic niches that had previously not existed. From all we can tell the ancient polymath Archimedes was a Von Neumann for his age. Archimedes seems likely to have been of aristocratic background, and part of the class of leisured intellectuals. The fact that he had such innate talent and disposition, combined with his life circumstances, was simple happenstance.

Today we live in a different age. Specialization, and the post-industrial economy, put a premium on competencies associated only with individuals on the “right tail” of the IQ distribution. Similarly, our genetic background predisposes many of us to obesity because the modern environment is “obesogenic.” The reality is that obesity was not an issue for almost all of human history, so genetic variation (often behavioral/cognitive) that is associated with obesity today was not so associated with it in the past. There could be no selection against obesity when it wasn’t a trait within the population.

Just as the modern environment is potentially “obesogenic,” it is also potentially “intelligenic.” Here’s what I’m talking about, The Science Behind Making Your Child Smarter:

The research also lends insight into why many apps and training programs aimed at raising IQ fail to produce lasting effects, says Elliot Tucker-Drob, an associate professor of psychology at the University of Texas at Austin, and co-author of the study.

Raising IQ may require the kind of sustained involvement that comes with attending school, with all the practice and challenges it entails. “It’s not like you just go in for an hour of treatment a week. It’s a real lifestyle change,” he says


To be a “nerd” is a lifestyle only possible in the modern information-rich environment. The Flynn effect is evidence that changing environments can shift the whole distribution. But just as with obesity or adult-onset diabetes risk, there is also heritable variation latent across the genome that seems to affect one’s response to the intelligenic environment.

Humans have large brains for our size. We are smarter than other primates. But evolutionary genetics today seems to be coming to the conclusion that it wasn’t a quantum jump, but gradual selection and change. Having a very low intellectual capacity was probably correlated with low fitness in the past (though small brains are calorically less greedy).

But, having a very high general intelligence does not seem to have resulted in that great of a gain in social or cultural status in comparison to being of normal intelligence. In fact, if the genetic correlation is such that it’s associated with some higher risk for mental instability, it could simply be that a form of stabilizating selection over time kept humans within the “normal range” because that was evolutionarily optimal. Be smart enough. But not too smart that you are weird.

And, as theorists from cultural evolution have observed, we are a “hive-mind” which leverages collective wisdom. Most of us don’t have to derive mathematical equations, we can use the formula provided to us. Though it’s useful to have a few people around who can invent statistics that the rest of us use…

Drawing on the slate of human nature

Some of you have been reading me since 2002. Therefore, you’ve seen a lot of changes in my interests (and to a lesser extent, my life…no more cat pictures because my cats died). Whereas today I incessantly flog Who We Are and How We Got Here: Ancient DNA and the New Science of the Human Past, in 2002 I would talk about Steven Pinker’s The Blank Slate: The Modern Denial of Human Nature quite a bit. The reason I don’t talk much about The Blank Slate is that some point in the 2000s I realized my future deep interests were going to be in population genetics, rather than behavior genetics and cognitive psychology. If you are not a specialist who doesn’t follow the literature. Who doesn’t “read the supplements”. You’re going to stop gaining anything more from books at a certain point.

Similarly, after I read In Gods We Trust: The Evolutionary Landscape of Religion, I read a lot of books on the cognitive anthropology of religion. Until I didn’t. Now that Harvey Whitehouse has teamed up with Peter Turchin, I suspect I’ll check in on this literature again.

But life comes at you fast. Today I think the broad thesis of The Blank Slate seems so correct, that we are not a “blank slate”, that no one would argue with that. Rather, the implications of that thesis are highly “problematic,” and social and cultural constructionism has really gone much further on the Left operationally than they were in the early 2000s. To give a concrete example, you can admit that sex differences are real and significant, but you have to be very careful in mentioning or highlighting specific instances or cases where they matter.

Moving to a more controversial topic, for a long while I’ve pretty much ignored the genomic study of the normal variation of cognition. The reason is that until recently all the studies were very underpowered to detect much of anything. The sample sizes were too small in relation to the genetic architecture of the trait because of the “Fourth Law of Behavior Genetics.”

As 2018 proceeds I think we can say that we are now in new territory. On Twitter, Steve Hsu seems positively ecstatic over a paper that just came out in PNAS. His blog post, Game Over: Genomic Prediction of Social Mobility summarizes it pretty well, but you should read the open access paper.

Genetic analysis of social-class mobility in five longitudinal studies:

Genome-wide association study (GWAS) discoveries about educational attainment have raised questions about the meaning of the genetics of success. These discoveries could offer clues about biological mechanisms or, because children inherit genetics and social class from parents, education-linked genetics could be spurious correlates of socially transmitted advantages. To distinguish between these hypotheses, we studied social mobility in five cohorts from three countries. We found that people with more education-linked genetics were more successful compared with parents and siblings. We also found mothers’ education-linked genetics predicted their children’s attainment over and above the children’s own genetics, indicating an environmentally mediated genetic effect. Findings reject pure social-transmission explanations of education GWAS discoveries. Instead, genetics influences attainment directly through social mobility and indirectly through family environments.

Why does this matter? I’m assuming most of you have seen charts like the ones below, which “prove” how the game is rigged against the poor:

The problem that most behavior geneticists immediately have with these popular analyses, which now suffuse our public culture (e.g., the “representation” argument in academic science often takes as a cartoonish model that all groups will have equal representation in all fields given no discrimination; substantively almost everyone believes this isn’t true in some way, but for the sake of argumentation this is a bullet-proof line of attack which every white male academic is going to retreat away from), is that they ignore genetic confounds. This paper is an attempt to address that. Measure it. Quantify it. Characterize it.

The two most interesting results for me have to do with siblings and mothers. Unsurprisingly siblings who have a higher predicted educational attainment score genetically tend to have higher educational attainments. As you know, siblings vary in relatedness. They vary in the segregation of alleles from their parents. Some siblings are tall. Some are short. This is due to variation in genetics across the pedigree. People within a family are related to each other, but unless you are talking Targaryens they aren’t exactly alike. Similarly, some siblings are smart and some are not so smart, because they’re “born that way.”

We knew that. Soon we’ll understand that genomically I suspect.

Second, we see again the importance of maternal effects and non-transmitted alleles. Mothers who have a higher predicted level of education have children with more education even if those children don’t inherit those alleles.* One natural conclusion here is mothers with a particular disposition shaped by genes are creating particular environments for their children, and those environments let them flourish even if they do not have their mother’s genetic endowments. This actually has “news you can use” implications in life choices people make in relation to their partners.

The study ends on a cautionary note. Residual population substructure can cause issues, correcting which can attenuate or eliminate such subtle and small signals. The sample sizes could always get bigger. And ethnically diverse panels have to come into the picture at some point.

But Razib abides. This study had a combined sample size of >20,000 individuals. Then you have the other recent paper with 270,000 individuals, Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. All well and good, but I wait for greater things. There is no shame in waiting for better things. And I prophesy that a greater sample size shall come to pass before this year turns into the new.

And you know what’s better than 1 million samples? How about 1 billion samples!

* Note that the models are controlling for a lot of background socioeconomic variables.

The GRE is useful; range restriction is a thing

The above figure is from Beyond the Threshold Hypothesis: Even Among the Gifted and Top Math/Science Graduate Students, Cognitive Abilities, Vocational Interests, and Lifestyle Preferences Matter for Career Choice, Performance, and Persistence. It shows that even at very high levels of attainment on standardized tests there are differences in life outcome based on variation. The old joke is that results on intelligence tests don’t matter beyond a certain point…that point being whatever your own position is! But these results show that mathematics SAT outcomes at age 13 can still predict a lot of things across a wide range.

From personal experience people outside of psychology are pretty unaware of the power of cognitive aptitude testing. This includes many biologists. I was reminded of the above figure as I read portions of Richard Haier’s The Neuroscience of Intelligence. If you are a biologist curious about the topic, this is a highly recommended book.

The main reason I am posting this is because a friend in academia suggested it might be useful. There has recently been a backlash against the GRE exam, with support from the highest echelons of the science media. Additionally, many researchers in public forums are expressing objections to the GRE very vocally. Naturally this has resulted in counterarguments…but respondents have to be very careful how the couch their disagreement, because they fear being accused of being racist, sex, or classist. Such accusations might trigger social media mobs, which no one wants to be the target of (and if past experience is any guide, friends and colleagues will stand aside while the witch is virtually burned, hoping to avoid notice).

Because of the request above I finally decided to look at the two papers which are eliciting the current wave of GRE-skepticism, The Limitations of the GRE in Predicting Success in Biomedical Graduate School and Predictors of Student Productivity in Biomedical Graduate School Applications. To my eye they suffer from the same problem as all earlier criticisms: range restriction.

The issue is that if a university is using the GRE and other metrics well as filters for those admitted then there shouldn’t be that much variation to be left to be explained by those measures (the outcome being publications or some other important metric which actually leads to the production of science, as opposed to test scores and grades). The two papers above look at those admitted to biomedical programs at UNC and Vanderbilt, while another study looked at UCSF. These are all universities with standards high enough that there are either explicit or implicit cut-off scores so that many students are removed from the applicant pool immediately (the mean scores are well above the 50th percentile, you can see them in the paper yourself).

When I was in graduate school I was on a fellowship committee for several years, and I had access to GRE scores and grades. But I didn’t really pay much attention to them because there wasn’t that much range. And to be honest if the student was beyond their first year I didn’t look at all as time went on. In contrast, I did look really closely at the recommendations from their advisors. From talking to others on the committee this seemed typical. Once students were admitted they were judged based on how they were doing in graduate school. And how they were doing in graduate school had to do with research, not their graduate school GPA or what they scored on the GRE to get in.

As an empirical matter I do think that it is likely many universities will follow the University of Michigan in dropping the GRE as a requirement. There will be some resistance within academia, but there is a lot of reluctance to vocally defend the GRE in public, especially from younger faculty who fear the social and professional repercussions (every time a discussion pops up about the GRE I get a lot of Twitter DMs from people who believe in the utility of the GRE but don’t want to be seen defending it in public because they fear becoming the target of accusations of an -ism). My prediction is that after the GRE is gone people will simply rely on other proxies.

If the GRE is not required, but can be taken, then students who do well on the GRE will put that on their application. Sometimes strong students encounter tragedies in their undergraduate years which strongly impact their grade point averages, and very strong GREs can help show admissions committees that they can do the coursework despite their undergraduate record (I’m not positing a hypothetical, but recounting real individuals I’ve known of and seen). It seems cruel to deny these students the chance to submit their test scores. This means that those professors who believe the GRE is valid will show preference to students who take the test and have strong scores (and to be sure, many more care about the GRE when it means someone concretely joining their lab, as opposed to the abstraction of who gets admitted to the department).

More broadly, professors who are taking students will look more at proxies for GRE score, such as undergraduate institution, or the prestige of the people writing recommendation letters. That is, pedigree will matter a lot more. In some places, such as Britain, standardized testing emerged in part as a way to identify strong students from underprivileged backgrounds. These are not the type of students who would ever be able to present a prestigious letter of recommendation. This is a sort of student which still exists (often they are from non-academic backgrounds, being the first to graduate from college in their family; what they lack in polish they compensate for in aptitude, but that takes the right environment to express).

The recourse to other variables besides the GRE score will likely have mixed results at best. Consider the successful campaign to ban asking for job applicants’ criminal records. It turns out that just increased discrimination against all young black men, because employers could not longer differentiate. In general I think removing the GRE would probably hurt graduates of less prestigious state universities the most (and of course students from East Asia, who tend to have a comparative advantage on standardized tests). I’m pretty sure we’ll see, as the experiment will be run.

Addendum: There are professors at relatively prestigious research universities who had mediocre or sub-par GRE scores. We all know them. To some extent I think many of these individuals almost take pride in the fact that they accomplished so much in science despite negative feedback due to their unimpressive test scores. But remember that we’re talking about trends and averages, not deterministic predictions. Nothing in science is guaranteed, and even if you start at Harvard with undergraduate publications (not first author, but still) in Nature you may not make it that far (I’m thinking of a friend of mine, alas, who picked the wrong lab/project and couldn’t recover).

Applying intelligence to genes for intelligence

Carl Zimmer has an excellent write up on the new new Nature study of the variants associated with IQ, In ‘Enormous Success,’ Scientists Tie 52 Genes to Human Intelligence.

The issue with intelligence is that it’s a highly polygenic trait for which measurement is not always trivial. You need really large sample sizes. It’s about ten times less tractable than height as a quantitative trait. There are still many arguments about its genetic nature (though a majority position that it’s not rare variants of large effect seems to be emerging).

But all in good time.

Science is divided into many different fiefdoms, and people don’t always talk to each other. For example I know a fair number of population genomicists, and I know behavior geneticists who utilize quantitative genomic methods. The two are distinct and disparate groups. But the logic of cheap sequencing and big data is impacting both fields.

Unfortunately when you talk to population genomicists many are not familiar much with psychology, let alone psychometrics. When it comes to the behavior geneticists many come out of psychology backgrounds, so they are not conversant in aspects of genetic theory which harbor no utility for their tasks at hand. This leads to all sorts of problems, especially when journalists go to get comments from researchers who are really opining out of domain.

Some writers, such as Carl Zimmer, are very punctilious about the details. Getting things right. But we have to be cautious, because many journalists prefer a truth-themed story to the truth retold in a story format. And, some journalists are basically propagandists.

Over the next five years you will see many “gene and IQ” studies come out, with progressively greater and greater power. Read the write-ups in The New York TimesScience, and Nature. But to my many readers with technical skills this is what you should really do:

  1. pull down the data.
  2. re-analyze it.

My plain words are this: do not trust, and always verify.

I’m a big fan of people educating themselves on topics which they have opinions on (see: population genetics). If intelligence is of some interest to you, you should read some things. Arthur Jensen’s classic The g Factor: The Science of Mental Ability can be quite spendy (though used copies less so). But Stuart Ritchie’s Intelligence: All That Matters and Richard Haier’s The Neuroscience of Intelligence are both good, and cheaper and shorter. They hit all the basics which educated people should know if they want to talk about the topic of intelligence in an analytical way.