The publication of Blueprint (2018) by the behavioral geneticist Robert Plomin has revived the old debate about whether there’s something inherently racist or right-wing about looking for biological causes of human behavior. The subtitle of Plomin’s book—How DNA Makes Us Who We Are—makes it sound as if he’s a full-blooded hereditarian and that has led to a predictable outcry from long-standing opponents of this “dangerous” intersection where the natural sciences and the behavioral sciences meet. (To read an extract from Blueprint, click here.)
To its opponents, sociogenomics—or social genomics—of which Plomin is a leading practitioner, sounds suspiciously like sociobiology. When the Harvard entomologist E.O. Wilson published a book of that name in 1975, it was greeted with passionate opposition by a group of left-wing scientists who had assembled under the banner of ‘Science for the People,’ originally an anti-Vietnam War protest group. The biologists in that organization, several of whom Wilson had counted as friends up until this point, formed the ‘Sociobology Study Group’ and started firing off venomous letters to newspapers. For instance, a letter in the New York Review of Books signed by Stephen J. Gould and Richard C. Lewontin, among others, accused Wilson of peddling the same junk science that had led to the murder of six million Jews:
The reason for the survival of these recurrent determinist theories is that they consistently tend to provide a genetic justification of the status quo and of existing privileges for certain groups according to class, race or sex. Historically, powerful countries or ruling groups within them have drawn support for the maintenance or extension of their power from these products of the scientific community…These theories provided an important basis for the enactment of sterilization laws and restrictive immigration laws by the United States between 1910 and 1930 and also for the eugenics policies which led to the establishment of gas chambers in Nazi Germany.
Wilson was dubbed the ‘Right-Wing Prophet of Patriarchy’ and subjected to vicious barracking whenever he crossed Harvard Yard or attempted to speak in public. The most famous protest occurred in 1978 at a symposium of the American Association for the Advancement of Science in Washington D.C. that had been convened to bring Wilson and his critics together. Ulicia Segerstrale takes up the story in Defenders of the Truth (2000), the definitive account of the sociobiology controversy:
The session has already featured Gould, among others, and Wilson is one of the later speakers. Just as Wilson is about to begin, about ten people rush up on the speaker podium shouting various epithets and chanting: ‘Racist Wilson you can’t hide, we charge you with genocide!’ While some take over the microphone and denounce sociobiology, a couple of them rush up behind Wilson (who is sitting in place) and pour a pitcher of ice-water over his head, shouting ‘Wilson, you are all wet!’
No one has yet emptied a bucket of water over Plomin’s head, but several critical articles have appeared, including one entitled ‘Blueprint—The Stealthy Return of Scientific Racism?’ To date, the most uncharitable review has been by Nathaniel Comfort, professor of the history of medicine at Johns Hopkins, which appeared in the scientific journal Nature. Entitled ‘Genetic determinism rides again,’ it begins as follows:
It’s never a good time for another bout of genetic determinism, but it’s hard to imagine a worse one than this. Social inequality gapes, exacerbated by climate change, driving hostility towards immigrants and flares of militant racism. At such a juncture, yet another expression of the discredited, simplistic idea that genes alone control human nature seems particularly insidious.
Comfort compares Blueprint to The Bell Curve (1994) and A Troublesome Inheritance (2014), two of the most controversial books in this field, whose authors he accuses of “leveraging the cultural authority of science to advance a discredited, undemocratic agenda.” Comfort goes on to describe Blueprint’s central hypothesis—that the DNA revolution will enable us to make huge strides in fields like medicine and education—as “old hereditarian wine pipetted into tiny polygenic bottles.”
Comfort doesn’t outright accuse Plomin of racism, but treats his failure to mention race (or intersectionality) as incriminating:
Blueprint does depart from much prior hereditarian social science in not explicitly mentioning race—the hot-button issue of many earlier works. It instead looks at class. Plomin uses a data set of mostly white British twins, most of whom attended English grammar schools. Yet, given Plomin’s extensive experience and his footnotes, the absence of any explicit mention of race (to disavow it, say, or to allude to intersectionality) is conspicuous.
That ‘damned if you do, damned if you don’t’ approach when it comes to finding evidence of racism is characteristic of those who see the spectre of eugenics haunting every genetics lab and I’ll return to it below. The sin Plomin is being accused of here may be ‘racial inexplicitness,’ a form of subterfuge that, according to critical race theorist David Gillborn, “allows hereditarian advocates to adopt a colorblind façade that presents their work as new, exciting and full of promise for all of society.” Incidentally, the data set Comfort is referring to in the above paragraph is the Twins Early Development Study (TEDS) and only a small minority of the twins in that sample attended grammar schools.
Another disgracefully smear-filled–not to mention factually sloppy–review of a genetics book from Nathaniel Comfort. Why do Nature keep asking this guy to write for them? https://t.co/QwNjk9U1st
— Stuart Ritchie (@StuartJRitchie) September 25, 2018
To assess whether Plomin is guilty of “determinism,” it helps to understand a little about polygenic scores, which much of his book is devoted to discussing. Studies of hundreds of thousands of individual genomes—known as genome-wide association studies, or GWAS—have enabled researchers to establish links between sites of genetic variation in particular populations —single-nucleotide polymorphisms, or SNPs—and particular phenotypic traits which vary from person to person, such as height and educational attainment. These links are known as polygenic scores. Armed with this information, geneticists (and direct-to-consumer genomics companies like 23andMe) can analyze the genome of a particular individual and make predictions about how tall that person is likely to be, how long they’re likely to remain in school, and so on. These predictions aren’t 100 percent accurate; rather, they’re expressed as percentiles or risk scores. So Plomin, for instance, is at the 90th percentile for height (he’s 6ft 5) and the 94th percentile for educational attainment (he’s a professor at King’s College London). The second largest GWAS to date was for years of education, or EduYears in the genetic jargon. It involved a sample size of over a million and found 1,271 SNPs associated with EduYears. A polygenic score based on this study predicts between 11 and 13 percent of the variance in educational attainment. That may not sound like much but it’s more than the variance predicted by many stand-alone environmental factors, such as parental education.
It should be obvious from the above that polygenic scores are probabilistic not deterministic, but in case that isn’t clear Plomin belabours the point: “Genetic influences are probabilistic propensities, not predetermined programming” (p.43); “Polygenic scores are useful for individual prediction only as long as we keep in mind that the prediction is probabilistic, not a certainty” (p.145); “Polygenic scores will always be probabilistic, not deterministic, because their ceiling is heritability, which is usually about 50 per cent” (p.150); “It is worth reiterating the mantra that polygenic scores are inherently probabilistic, not deterministic” (p.151); “It is important that parents are not fatalistic about their children, because polygenic scores are probabilistic not deterministic” (p.154); etc. How Comfort can accuse Plomin of “genetic determinism,” or of believing that “genes alone control human nature,” given his constant repetition of this “mantra,” is a mystery.
What seems to have convinced Comfort that Blueprint is “insidious” is Plomin’s claim that “genetics is the main systematic force in life.” What Plomin means by this is that while most human traits are no more than 50 percent heritable—that is to say, no more than half the phenotypic variance is linked to genetic variance—the salient aspects of the environment are not those experiences we share with our siblings, such as our parents’ socio-economic status, their approach to parenting, the neighborhood we’re brought up in or the schools we go to. Plomin has assembled a mass of research evidence, based on twin, adoption and family studies, showing just how little effect the shared environment has. “The astonishing implication from this research is that we would be just as similar to our parents and our siblings even if we had been adopted apart at birth and reared in different families,” he writes in Chapter Seven (‘Why children raised in the same family are so different’).1 In his most recent research, he has incorporated polygenic scores into the study designs. For instance, he worked on a study involving a U.K.-representative sample of 4,814 students that showed the type of school British children attend accounts for less than one percent of the variance in their exam results once you control for general cognitive ability, prior attainment, parental socio-economic status and polygenic score for EduYears. (Full disclosure: I was one of the co-authors of that study.)
Families and schools are what we think of as “nurture” and one interpretation of Blueprint is to see it as a salvo in the ongoing nature-nurture debate—a devastating, war-winning salvo. But it doesn’t follow that Plomin thinks the environment, as distinct from nurture, has no effect on the way people turn out. The environmental inputs that matter most, according to him, are what he calls our “non-shared” experiences—“unsystematic, idiosyncratic, or serendipitous events,” often mediated by our genetic predispositions. So when Plomin says genetics is by far the greatest systematic force in making us who we are, he isn’t saying the environment has no effect. It’s just that the environmental inputs that do have an impact are, for the most part, unsystematic.
“We now know that DNA differences are the major systematic source of psychological differences between us,” he writes in the ‘Prologue.’ “Environmental effects are important but what we have learned in recent years is that they are mostly random—unsystematic and unstable—which means that we cannot do much about them.”
This has far-reaching implications, many of which threaten to lay waste to vast areas of intellectual endeavor. Freudian psychoanalysis, for instance, is clearly bunk, as is most child psychology (unless it’s Judith Rich Harris patiently explaining why parents have little effect on the way children turn out). Parenting manuals? Not worth the paper they’re printed on.
What about education reform? That’s a tough one for me because I’ve devoted nearly a fifth of my life to trying to improve English public education, including co-founding four schools. But the implication of Plomin’s research is that it’s extremely hard, not to say impossible, for governmental agencies and charitable bodies to design systematic interventions, whether in early childhood or adolescence, that will reduce the attainment gap—which may explain why nearly all such attempts have failed. In fact, if you drive up standards in under-performing schools, the effect would be to increase the overall variation in attainment due to genes since if you equalize the environment you will increase the influence of genes, making exam results more, not less, heritable.
The most generous thing Plomin can bring himself to say about schools is that they matter, but they don’t make a difference. Don’t make a difference. There go the last 10 years of my life—poof. To paraphrase another scientist called Robert, Plomin is like Vishnu, a destroyer of worlds.2
But is he a social Darwinist? Critics of sociogenomics, like critics of sociobiology, usually take it for granted that anyone looking for biological influences on human behavior—coming down on the side of nature in the nature-nurture debate—is attempting to justify the status quo. That is, they assume that the scientist in question is committing the naturalistic fallacy: what is, ought to be. And one of the puzzling things about this debate is that it doesn’t matter how often the researchers in the dock deny this, they simply cannot disabuse their accusers of this notion. The most their critics will allow is that even if they aren’t making this link, their findings will be leapt on by Randian, free market evangelists—or members of the alt-Right—who are more prone to this type of faulty reasoning. But the accusers, too, often have difficulty uncoupling the normative from the descriptive. You might say they’re guilty of the moralistic fallacy—of believing that something cannot be true if it has unsettling moral implications. That could explain why they spend so much time trying to debunk the findings of researchers in this field—which doesn’t feel like a very wise strategy. After all, if the science the progressive liberals are trying to deny turns out to be true—and the evidence is pretty overwhelming—that will suggest to their political opponents that their beliefs are justified. Wouldn’t their energy be better spent making it clear that the moral case for a more equal society isn’t contingent on a particular conception of human nature, particularly not one so vulnerable to genomic revelation?
E.O. Wilson couldn’t have been clearer in his disavowal of social Darwinism, which he referred to as a “dangerous trap”:
The moment has arrived to stress that there is a dangerous trap in sociobiology, one which can be avoided only by constant vigilance. The trap is the naturalistic fallacy of ethics, which uncritically concludes that what is, should be. The “what is” in human nature is to a large extent the heritage of a Pleistocene hunter-gatherer existence. When any genetic bias is demonstrated, it cannot be used to justify a continuing practice in present and future societies.
Similarly, in Blueprint Plomin makes it clear that he doesn’t believe his findings can be used to justify socio-economic inequality. In the chapter entitled ‘Equal Opportunity and Meritocracy’, he writes:
Much of the concern about inequality and social mobility is about income inequality. Individual differences in income are, like everything else, substantially heritable, about 40 percent. Income correlates with intelligence, and genetics drives this correlation. But this does not mean that higher intelligence merits more income. I would argue that genetic wealth is its own reward. If society really wanted to reduce income inequality, it could do so directly and immediately with a tax system that redistributes wealth.
Plomin is insistent that no policy prescriptions follow from his research, or genetic research in general, since policies depend on values. But I would qualify that slightly. While science cannot tell us which ends to pursue, it can inform our choice of means and that is as true of social genomics as it is of aeronautical engineering. For instance, if you’re aim is to maximize your kid’s chances of getting into a top college, helicopter parenting probably isn’t going to help. Plomin calls the idea that your child’s future depends on how hard you push them an “illusion” and urges parents to “relax and enjoy their relationship with their children without feeling a need to mold them.”
More generally, behavioral genetics teaches us that if your goal is end-state equality, it’s naïve to think the state can just “wither away” after a massive redistribution of wealth and power has taken place. We know from the work of Plomin and others that one of the major sources of socio-economic inequality is the unequal distribution of genetic wealth, and that won’t be affected by the initial levelling. So the state will have to constantly intervene if the egalitarian utopia is to be preserved, drastically curtailing human freedom. That may be a price that some equalitarians are willing to pay—that’s a value-driven choice, not a scientific one. But the fact that scientists in this field have amassed so much evidence that human beings most definitely aren’t tabula rasa may be the underlying cause of the hostility they provoke from those whose political beliefs depend on the blank state hypothesis. The biologists who led the charge against Wilson, for instance, were all Marxists.
What About Race?
Is there something sinister about social genomics nevertheless that’s likely to resuscitate the corpse of race science and give succor to ethno-nationalists? Another review by Nathaniel Comfort in Nature, this one an out-and-out rave of a book called Social by Nature by Catherine Bliss which is highly critical of sociogenomics, was headlined ‘CRISPR’s Willing Executioners’. Not too subtle, that. In her book, Bliss wrings her hands with alarm at the “shocking parallels between sociogenomics and older, discredited sciences” and accuses genetic researchers of using essentialist language that “gives validity to unwarranted biological notions of race” and ignores the “structural” forces that prop up white privilege. But beyond these routine gripes, which will be familiar to anyone acquainted with the field of critical science studies, Bliss doesn’t flesh out why she thinks genomicists are doomed to repeat the mistakes of their eugenicist forebears. Yes, they share a genealogy, but as Plomin might say, the effect of that shared history is probabilistic, not deterministic.
In this thread I will tweet some of the errors observed while reading Catherine Bliss's new book about social science genomics, Social by Nature. (I'm interviewee #9 in the book, btw.)
— Jeremy Freese (@jeremyfreese) January 16, 2018
Exhibit A in the case for the prosecution against Plomin is the fact that he was one of the signatories of the ‘Mainstream Science on Intelligence’ letter published in the Wall St Journal in 1994. Signed by a total of 52 intelligence researchers, it was a response to those critics of The Bell Curve who attempted to portray Charles Murray and Richard Herrnstein as a couple of cranks on the outer fringes of the scientific community. The letter didn’t defend every claim in the book, but it confirmed that the authors’ summary of the science on intelligence was not some wildly distorted picture designed to further a racist agenda but reflected the mainstream consensus.
Plomin’s role in that affair has been brought up by at least one critic trying to find a covert racist agenda concealed between the lines of Blueprint (although not by Bliss or Comfort) so it’s worth pointing out that The Bell Curve is not the white supremacists’ manifesto it is often portrayed as being. Only one chapter in the book broaches the subject of whether ethnic differences in average IQ are genetically influenced, and if the authors’ object is to give succor to white nationalists they don’t do a great job since they point out that East Asians and Ashkenazi Jews have higher average IQs than whites. On the vexed issue of black-white disparities in intelligence, Murray and Herrnstein are painstakingly even-handed and their conclusion, based on their parsing of the evidence, is that the difference is likely to have something to do with both genes and the environment. “What might the mix be?” they ask. “We are resolutely agnostic on that issue; as far as we can determine, the evidence does not yet justify an estimate.”
Plomin provides no clue as to what he thinks on this issue, but the fact that he doesn’t explicitly repudiate Murray and Herrnstein’s hypothesis cannot be taken as a tacit endorsement, as Comfort implies. The focus of Plomin’s research has been about disentangling the effects of genes and the environment on individual differences; he has almost nothing to say about group differences in Blueprint other than to stress that his findings about the former are not applicable to the latter. “It is an important principle that the causes of average differences between groups are not necessarily related to the causes of individual differences within groups,” he writes in the book’s endnotes.
This principle also applies to more politically sensitive differences between groups, such as average differences between males and females, between social classes, or between ethnic groups. The causes of average differences are not necessarily related to the causes of individual differences. For example, some of the biggest differences between the sexes are found in childhood psychopathology—boys are many times more likely than girls to be hyperactive or to have autistic symptoms. However, these symptoms are highly heritable for both boys and girls, and genetic studies show that the same genes affect boys and girls. Although DNA differences are substantially responsible for individual differences in these symptoms, they do not appear to account for the average difference between boys and girls. What does account for the average difference? We don’t yet know.
When Plomin says the causes are not necessarily related is he allowing that they could be? The fact that systematic environmental inputs—parental socio-economic status, zip code, school quality, etc.—have a negligible effect on individual differences could lead some people to hypothesize that they might not have much impact on group differences either. You can imagine how a race realist might make use of that data to argue that mean differences in IQ between ethnic groups is unlikely to be explained by differences between their shared environments. Indeed, you could design a research study that tested that hypothesis, although it would not be easy and the databanks that Plomin makes use of contain very few children of non-European ancestry. (Ninety-two per cent of the children in TEDS are white.) There are also a host of complicated technical difficulties with group-difference studies, including what’s known as ‘measurement invariance’—the process of checking whether tests are measuring the same thing in different groups, and thus whether heritability estimates in one group can realistically be compared to those in others. In any event, you can be confident that Plomin isn’t going to go there. His agnosticism is even more resolute than Murray and Herrnstein’s: we simply don’t know what accounts for average differences between groups and he isn’t about to throw any light on the matter. His interest is confined to the etiology of individual differences.
Can GWAS Tell Us Anything About Black-White IQ Differences?
Will this question eventually be answered by genome-wide association studies? As the sample sizes multiply and the number of SNP ‘hits’ for EduYears soars beyond the 10,000 mark, will we learn what role genes play, if any, in black-white IQ differences? The answer is probably not.
There’s a simple reason for this and a not-so-simple one. The straightforward reason is that the genomic data used in GWAS are predominantly drawn from populations of European ancestry. A 2009 study found that 96 percent of GWAS participants were of European descent. When the same researchers updated their study seven years later, they found the proportion of individuals included in GWAS not of European descent had increased to nearly 20 percent, but much of this rise was due to more populations of Asian ancestry being included – the percentage of people of African and Latin American ancestry, Hispanic people and indigenous peoples had barely changed. So even though geneticists have identified over 1,000 SNP ‘hits’ for EduYears, the million-plus people in that particular GWAS were overwhelmingly of European ancestry.
Does that matter? As Richard C. Lewontin argued, human populations are “remarkably similar to each other”—we share about 99.5 percent of the same genes. So once you have a polygenic score that predicts between 11-13 percent of the variance in educational attainment for a particular population, why can’t it be applied to ever-so-slightly different populations to see if there are average differences between them? This is where it gets a bit more complicated. The short answer is it can, but it loses much of its statistical power. Populations may not differ from each other a great deal, but they are sufficiently different to make GWAS findings non-generalizable. The set of SNPs linked to years of education in, say, people of African ancestry are different to those for people of European descent.
There was a nice illustration of this point in a recent essay on social genomics by the Stanford sociologist Jeremy Freese. He discussed the efforts of a group of researchers to try and apply a polygenic score for height to a West African population:
The researchers took GWAS results for height, based on European-descended samples, and applied them to simulated European and West African populations based on established reference panels of gene frequencies for these populations. Startlingly, this work showed there was very little overlap in distributions: that is, nearly all West Africans would have lower polygenic scores for height than nearly all Europeans. So a näıve analyst given racially diverse data might conclude that polygenic score information was revealing the genetic basis of why West Africans are shorter than Europeans. But this cannot be right, because we know from the anthropological record the actual height distributions between these populations are not so different.
If you substitute “years of education” for “height,” you can see the difficulty of using polygenic scores to try and answer the question of whether ethnic differences in IQ are genetically influenced. And the problem will persist even when we have more diverse genomic data. Where we’re likely to end up is knowing which SNPs are associated with EduYears in population A and which are associated with EduYears in population B, but because the two sets of SNPs will be different we won’t be able to make a meaningful comparison between A and B.
Genetic Research Biased Towards Europeans
The fact that GWAS findings cannot be generalized across different populations—and polygenic scores are derived from a racially homogenous group, for the most part—is a hot-button issue in genomics because it means people of non-European ancestry will miss out on the benefits of the forthcoming biomedical revolution. For instance, if I know my polygenic risk score for cardio-vascular disease is in the 95th percentile, I can make various lifestyle adjustments to reduce the likelihood of having a heart attack. But the same data would be of no use to my Middle Eastern neighbor. The Guardian ran a piece about this recently entitled ‘Genetic research biased towards Europeans’ that quoted from a letter that Professor David Curtis, a geneticist and psychiatrist at UCL, had written to the leaders of the Medical Research Council and the Wellcome Trust flagging up this issue. “U.K. medical science stands at risk of being accused of being institutionally racist,” he wrote.
The causes of this bias are complex, but it’s worth noting that the efforts of genetic researchers to collect data from diverse populations about 20 years ago were frustrated by anti-racist social science activists. (H/t Jeremy Freese.) The Human Genome Diversity Project (HGDP) was attacked by various social scientists who were concerned that a policy of collecting genetic data from different ethnic groups would lend scientific respectability to the idea that essentialist racial categories have some basis in biological reality and aren’t just social constructs. At one point, an anthropologist compared the head of the HGDP to Joseph Mengele.
The question of whether vernacular racial categories are scientifically useful is almost as highly-charged as the issue of black-white IQ differences and the two are closely related since one way of short-circuiting any speculation about the causes of those differences is to deny that the racial distinction is scientifically valid. While it’s true that the standard racial categories don’t exactly correspond to genetic population clusters and have been shaped by a complicated array of social, economic and historical forces, nevertheless they map on to each other pretty well. In the U.S., genetic information statistically predicts people’s self-reported ethnicity with a good deal of accuracy. In this study, for instance, the correspondence between various genetic markers and people’s self-reported racial identity (white, African-American, East-Asian and Hispanic) was “near perfect”. For a deep dive into these murky waters, see this Quillette piece by Bo Winegard and Brian Boutwell.
The anti-racist activists in the academy want to have it both ways. Twenty years ago, they argued it would have been wrong to collect genomic data from populations of African ancestry since that would have been tantamount to admitting that we’re not all genetically identical under the skin. Today, the fact that people of non-European descent are going to miss out on the medical benefits of GWAS-derived polygenic risk scores is itself a manifestation of racism in biomedical research.
Those scientists who want to draw attention to the racial bias in genetic research but who don’t want to acknowledge the scientific validity of race are in a tricky position. I suppose professor Curtis could argue that it would have been possible to collect genomic data from diverse populations 20 years ago without acknowledging the scientific reality of race. The researchers could have used the word “population” instead and sorted the samples according to genetic groupings that didn’t correspondent to vernacular racial categories –not exactly, anyway. But if you’re unhappy with genetic researchers for failing to do that, or the institutions that fund them, it doesn’t seem fair to label them “racist”. After all, you cannot chastise them for leaving out non-European “races” without invoking essentialist categories that, had they used them 20 years ago, probably would have led you to calling them “racist”. Indeed, they were called “racist” for committing precisely that sin. The most you can reasonably accuse them of is being “populationist”—or something.3
There are parallels here with the medical costs of insisting that gender is a social construct, something Claire Lehmann wrote about in Commentary last year. In 2013, the FDA finally acknowledged something it had known for 20 years, which was that women metabolized the active ingredient in Ambien at half the rate of men, and it recommended cutting the dose in half for women. A team of researchers at Scripps Health in San Diego estimated that in 2010 alone, Ambien and similar sleeping pills had contributed to 500,000 “excess deaths” in the form of accidental overdoses, car crashes and falls.
It would be ironic if people of non-European ancestry permanently miss out on the polygenic breakthroughs in preventative medicine because professors in critical science studies – even some actual scientists – insist that race is a social construct and accuse anyone who dissents from this orthodoxy of tacitly endorsing white privilege. That was the fate meted out to David Reich, the Harvard geneticist, after he wrote a measured op ed in the New York Times entitled ‘How Genetics Is Changing Our Understanding of “Race”’. Sixty-seven scientists and researchers immediately fired off a ‘we, the undersigned’ letter to Buzzfeed, chastising him for unwittingly perpetuating “hierarchies of race, sex and class.” Inevitably, they saw parallels between Reich’s op ed and “racially restrictive immigration laws in 1924” and even gave him a wrist slap for casually using terms like “male” and “female” without acknowledging the social construction of gender. Both Nathaniel Comfort and Catherine Bliss were among the signatories.
Old Whine in New Bottles
Four years before E.O. Wilson published Sociobiology, Richard Herrnstein, then a professor of psychology at Harvard, published an article in the Atlantic Monthly entitled ‘IQ’ in which he argued that in societies where intelligence is increasingly linked to socio-economic status, as it is in America, there is a tendency for hierarchies to become genetically underpinned, thereby hampering movement from one class to another. He wasn’t celebrating this fact—on the contrary, he was sounding the alarm. But it didn’t take long for a pitchfork-wielding mob to assemble in Harvard Square. Protests were organized by Students for a Democratic Society and undergraduates were urged to ‘Fight Harvard Prof’s Fascist Lies.’ ‘Wanted’ posters started to appear around campus in the old Western style, with the words ‘Wanted for Racism’ emblazoned above a black-and-white picture of Herrnstein. According to the poster, he was wanted “for the fraudulent use of ‘science’ in the service of racial ‘superiority,’ male supremacy, and unemployment.”
For more than 50 years it has been impossible to talk about the biological influences on human behavior without provoking a hysterical reaction from the left and I’m afraid Robert Plomin’s Blueprint, which is a strong contender for science book of the year, is no exception. It’s old wine in new bottles, alright. But it should be spelt W-H-I-N-E. As Noah Carl has pointed out, much of the progressive left’s opposition to sociogenomics seems to be predicated on the belief that more harm than good will come from a scientifically-informed discussion of the links between genes and various psychological and medical traits, particularly if racial differences are introduced, and therefore it is justified in stifling this debate. But there’s scant empirical evidence that, provided it is informed by robust scientific research, this discussion will cause harm and several reasons to believe that suppressing it will.
Toby Young is an associate editor of Quillette.
1 Some adoption studies find non-trivial effects of the shared environment on some traits, e.g. this one and this one.
2 There’s some evidence from twin studies that the shared environment does matter for educational attainment, even if it doesn’t much matter for other traits like intelligence. Plomin estimates that school shared environments account for about 20% of the variance in exam performance.
3 For more on the potential medical harm resulting from treating race as purely a social construct, see here, here and here.