Race does not stand up scientifically, period. To begin with, if race categories were meant primarily to capture differences in genetics, they are doing an abysmal job. The genetic distance between some groups within Africa is as great as the genetic distance between many “racially divergent” groups in the rest of the world. The genetic distance between East Asians and Europeans is shorter than the divergence between Hazda in north-central Tanzania to the Fulani shepherds of West Africa (who live in present-day Mali, Niger, Burkina Faso, and Guinea). So much for Black, White, Asian, and Other.
Armed with this knowledge, many investigators in the biological sciences have replaced the term “race” with the term “continental ancestry.” This in part reflects a rejection of “race” as a biological classification. Every so-called race has the same protein-coding genes, and there is no clear genetic dividing line that subdivides the human species. Another reason for using the term “continental ancestry” in lieu of “race” is improved precision for locating historical and geographic origins when we look at the genome. Thus, continental ancestry allows for more genetically accurate descriptors. For example, President Barack Obama was not just the first socially “black” president. He was also the first (as far as we know) who has European and African ancestry.
Genetic differences are a potential—but highly unlikely—explanation for national, racial, or ethnic differences in behavior and success.
In sum, racial categories now in use are based on a convoluted and often pernicious history, including much purposefully created misinformation.
It is a good time, then, to dispel some myths about genetic variation that have been promulgated by both the left and the right alike. On the left, many try to discredit the notion that genetic variation underlies group differences by pointing out that there is more genetic variation within these groups than between them. Another favorite approach is to cite the fact that all humans are 99.9 percent genetically identical and that no group of humans has a gene (i.e., a coded-for protein) that another group lacks. Both of these arguments are canards. After all, we are also 98-plus percent identical to chimps and 99.7 percent similar to Neanderthals. Oh, what a difference that 2 percent (or 0.3 percent) makes!
Simply stated: Overall genetic variation tells us less than specific differences that matter. Imagine a group of humans that had a mutation in the FOXP2 gene—often called the language gene—such that this transcription factor (a gene that helps stimulate the expression of select other genes) was nonfunctional. These humans would lack the ability to communicate through language. In fact, this gene’s significance was first discovered through the study of an English family in which half the members across three generations suffered from severe developmental verbal dyspraxia—they could not communicate orally. This family could be 99.9999 percent genetically identical to their neighbors, but what a huge difference that 0.00001 percent makes. This criticality of particular genetic differences, as opposed to global similarity, is not unique to humans. Through genetic manipulation of just four genes, scientists in the lab have been able to turn a mustard weed into a woody tree. It sounds like a genetic version of the 1970s game show, Name That Tune: In how few notes (or genes) can one radically alter the phenotype of an organism?
Highlighting the fact that all humans share the same genes ignores the fact that much of evolutionary change and biological difference is less about the development of novel proteins (i.e. genes) than it is about the regulation of those genes’ expression—that is, the extent, the timing, and the location of when and where they are turned on and off. In fact, when the Human Genome Project first began, the number of human protein-coding genes was anticipated to be on the order of 100,000. After all, we are certainly more complex than Zea mays (corn) with its 32,000 genes, are we not?1 As it turns out, we have a mere 20,000 genes (or fewer). So most human difference is driven by the turning on and off of those 20,000 genes in specific tissues at particular times. The same ones may be expressed in the brain and in the liver. They may get switched on by an attacking bacterium and silenced by a hot meal. Each one is like a multitasking parent balancing home and office.
The fact that we all share the same genes does not rule out the possibility of important differences based on variation in the regulatory regions of the genome (promoters, enhancers, micro), RNAs, and other molecular switches. A better question than whether or not we have different proteins is whether or not we have different alleles. An allele is simply a version of DNA. It could be a single nucleotide that differs in the population at a given location (i.e. A, C, T, or G). Or it could be what geneticists call a copy number variant (such as when I have a stretch of ATG ATG ATG but you have five copies of that motif). When we ask if there are alleles that one population has that are not seen in any other population—the parallel question to the unique genes inquiry—the answer turns out to be yes. In fact, it is African populations that have the most “private” (i.e., unshared) alleles. This is a reflection of the greater diversity in sub-Saharan Africa compared with those groups who suffered the population bottleneck in the migration out of Africa. But the point is that there is no a priori reason to rule out the potential impact of these private alleles in explaining group differences.
It’s a good time to dispel myths about genetic variation that have been promulgated by both the left and the right.
A third argument that the left makes to discredit any genetic basis for observed group differences is that there has not been enough time—evolutionarily speaking—for meaningful differences to emerge. Stephen J. Gould is famously quoted as saying, “There’s been no biological change in humans in 40,000 or 50,000 years. Everything we call culture and civilization we’ve built with the same body and brain.” According to this viewpoint, human evolution more or less ended with the emergence of anatomically modern humans in the Rift Valley. After all, 60,000 years is but the blink of an eye compared with the entire history of hominids. And when we get to parsing differences between groups outside of Africa, that time span drops even more dramatically.
However, crucial group differences can emerge not just through positive selection for novel mutations, but also through selection on traits that are highly polygenic, for which there is plenty of genetic variation already in the genome on which to selectively sort and reproduce. We already know that height and cognitive ability are highly polygenic, influenced by thousands of small differences in the human genome. If those who are the smartest reproduce at higher rates than the less bright, an overall genetic shift in the IQ distribution could be achieved in a matter of a few generations (assuming that the reproductive and survival advantages of IQ were strong enough).2 In this view, 60,000 years is not a blink but an eternity.3 So if there were differential fertility and survival premiums to different behavioral traits—not just IQ but also trust, grit, self-regulation, and so on—we could easily witness genetic divergence across the millennia.4
Indeed, this is exactly what some controversial scholars such as the anthropologists Gregory Cochran and the late Henry Harpending have argued in their book, The 10,000 Year Explosion. They posit that the Neolithic Revolution and rise of settled civilizations led to a condition in which human social arrangements—as opposed to the natural landscape—became the primary driver of changes in population genetics. The result, they argue, is that many differences today can be traced to the accelerated selective pressure that agrarian society introduced. Such pressure favors mental traits like advanced planning at the expense of physical endurance and other traits that would be more advantageous to hunter-gatherers. The time since the development of agriculture in a given society, they argue, is a good predictor of how the genetic landscapes of different populations have adapted to these altered demands for survival. Their case, while plausible, has not been made with the data at hand but instead represents a narrative that relies on circumstantial evidence. Although recent research suggests that evolution has not “stopped” due to technological and social progress; we do not know what forces drive recent selection or what effect they may be having in the contemporary world.5 In other words, yes, humans are still evolving and genetically diverging from each other; however, claiming that the survival and reproductive gradients are different by continental and subcontinental locations—particularly with respect to social and mental skills—is unsupported by data.
The left does not have a monopoly on substituting assertion for evidence when it comes to human evolution. The right does a great job peddling its own untruths. Authors like Nicholas Wade, in his book A Troublesome Inheritance, focus on genotypes at one locus that display significant ethnic differences as a way to explain differences in group outcomes. It is not that a single gene cannot have a huge effect as FOXP2 does, it’s just that the ones that have demonstrated frequency differences by “racial” groups simply do not. Wade and others often discuss the MAOA copy number variant as the “warrior gene” because early candidate gene studies showed that this allele’s presence predicted violent behavior. They then point out that the “violent” allele is found at higher frequencies in the black population. However, such candidate gene studies—and this one in particular—have not withstood replication tests. And even if they did, the allele explains a trivial amount of the variation in the measured outcomes, so it is hardly a solid foundation on which to build a genetic model of group differences in behavior.
A second mistake of the right is to give too much credit to natural selection and too little to genetic drift.6 The former, in which genetic variants provide a survival advantage, could theoretically lead to gene-based accounts of differences across groups. The latter, in which genetic variation is not tied to advantage but instead is a random process that “tags” groups based on geography and historical time, can differ by group whose phenotypes like height or IQ can also differ but for environmental reasons that are spuriously correlated with the genetic differences.
We can see that purifying selection has occurred to accommodate the various environmental landscapes that humans have encountered as they fanned out across the globe. Very obvious examples include the prevalence of the sickle cell genotype—with its protective effect against malaria—which is present only in West and Central African populations, which have among the highest incidences of malaria in the world. Or the clear gradation in dermal melanin (skin tone) as predicted by distance from the equator and its intense sun exposure. Or even by body morphology, as evidenced by Allen’s Rule, which suggests that in colder climates, warm-blooded organisms will tend to have shorter, stockier builds to preserve heat, whereas in hotter climes, big ears, noses, and limbs allow for better heat loss through a higher ratio of surface area to body mass.
The mistake that many genetic determinists make is assuming that because we can observe this clear relationship between environment and genetics in some physical characteristics, we can unproblematically expand it to highly complex human behaviors and mental characteristics. That we can see selective pressures at work in generating phenotypic differences in traits that rely on a small number of genes—such as skin tone, eye color, or lactose tolerance—does not easily translate to a clear relationship between a highly polygenic trait such as cognitive ability and the social or physical landscape. For example, when discussing body size, we can observe limb-length variation in human populations as predicted by Allen’s Rule, but limb size is much less polygenic (it is largely controlled by a series of HOX genes) than is overall height.7 And indeed, height fails to show the latitude-phenotype relationship as clearly. Compare Pygmies and Bantus (who occupy a similar relation to the equator) or Inuit and Swedes (who also live at more or less the same latitude). This does not mean that a highly polygenic trait cannot be subject to intense selective pressure; just ask chicken breeders who have quadrupled poultry weights in 60 years.8
In addition to the complex and polygenetic structure of many behaviors at one point in time, rapid changes in economic fortunes during the last 50 years make simple genetic explanations of relative success by ethnic groups in the modern world all the more dubious. Although the last 10,000 years is certainly a plausible amount of time for geographic differences in the genetic architecture that shapes socioeconomic outcomes to emerge, 200 years is probably not, and 50 years is most definitely not. Yet we have seen Taiwan and South Korea, for example, go from poor societies with populations that could barely survive to countries with some of the highest living standards in the world.9 Thus, there are probably better accounts than genetic ones for explaining geographic variation in standards of living and associated social outcomes, explanations such as institutional differences in the rule of law and so on. For now, research and theory suggest that genetic differences are a potential—but highly unlikely—explanation for national, racial, or ethnic differences in behavior and socioeconomic success, but such an explanation is a very difficult case to make.
That said, let us ask what is perhaps the most controversial question in the human sciences: Do genetic differences by ancestral population subgroup explain observed differences in achievement between self-identified race groups in the contemporary United States over and above all the environmental differences that we also know matter? In their best-selling 1994 book, The Bell Curve: Intelligence and Class Structure in American Life, Richard Herrnstein and Charles Murray indeed made the argument that blacks are genetically inferior to whites with respect to cognitive ability. Their “evidence,” however, contained no molecular genetic data, and was flawed as a result. But today we have molecular data that might potentially allow us to directly examine the question of race, genes, and IQ. We raise this pernicious question again only to demonstrate the impossibility of answering it scientifically.
If Herrnstein and Murray redux wanted to proceed, perhaps an obvious way would be to examine whether all the small differences across the genomes of the average black and average white person in a dataset “add up” in a way that suggests that one group has, on average, genetic signatures that predict higher levels of important phenotypes, such as educational attainment. There are at least two ways of “adding up” genomes. The first is to use polygenic scores. The second is the use of principal components. Both have serious drawbacks.
Even if genes predict racial differences in IQ, they could do so because genes are good predictors of treatment in society.
A polygenic score is a single number that captures the sum total of thousands of little effects in the genome on a given trait. It is constructed by running a million or more separate comparisons for each place along the 23 pairs of chromosomes where there is variation (i.e. you have an A-A and I have a G-A) measured in a dataset. When summed, these measures can predict—albeit noisily—the distribution of a given phenotype in the population. The best performing polygenic score to date is for height. A single number calculated from someone’s DNA can explain about 50 percent of the variation in actual height in the population. A score that has been developed for education (and cognitive ability) can explain about 7 percent of the variation in years of schooling, according to a 2016 Nature study, and that score has since been refined to improve its predictive power. So while these are not explaining all of the genetic variation (we think height is about 80 percent genetic and education is at least 25 percent genetic), they do predict. Someone at the upper end of the education distribution is likely to get more than two more years of schooling on average than someone at the bottom of the pack (lowest 10 percent) in terms of his or her polygenic score.
As it turns out, however, these scores when developed for one population—say, those of European descent—fail to predict for other populations. Take the height example. The best height score, which has been “trained” on whites, when applied to blacks, predicts that Africans or African Americans are six inches shorter than they are. So they simply don’t work. The very differences in genetics between ancestral groups make comparisons across groups impossible. The million or so markers measured by gene chips are picking up different things in distinct populations. They are merely flags spaced out along the chromosomes and meant to stand in for all the genetic real estate around them. But what that real estate holds is very different—particularly when African descent populations, with their greater degree of variation, are compared to non-African populations. So polygenic scores, while useful for analysis within populations, do not allow us to make apples to oranges comparisons across groups.
A second approach would be to measure what are called principal components. This is a measure that quantifies genetic ancestry from the overall patterns of variation in the data. What if we gave up on polygenic scores and instead predicted IQ by the percentages of different genetic ancestries as indicated by an individual’s scores of principal components? For example, the average African American has 10 percent European genetic ancestry. Some whites have some African ancestry, whether they know it or not. Shouldn’t the proportion, then, of someone’s genome, his or her percentage of African or European ancestry, predict socioeconomic or cognitive outcomes?
The problem is the same one facing Wade (even if he was unaware of it): Whether measured with a single genetic marker or a summative measure like a principal component, genes act as proxies for environments. The only way to truly insure that observed differences by genetics are really genetic effects is to compare full siblings from the same family where we know the differences between brothers and sisters are the result of luck, of the randomness at conception, and not correlated with background differences in poverty, neighborhood, and so on. But here’s the catch-22: While polygenic scores vary quite a bit between siblings, measures of ancestry, almost by definition, do not. Thus, while initially promising, the idea of comparing siblings with differing dosages of continental ancestries won’t work either.
Even if we had figured out a way to factor out all the cultural, historical, and economic differences that correlated with genetic ancestry, and found an effect, such a result would still raise the question: How? While it may or may not be true that brain development pathways could be implicated in test score differences, it is almost surely true that the percentage of African or European ancestry predicts physiognomy. That is, even within families, we are willing to wager that the sibling with more African genes is also the sibling with darker skin, curlier hair, and more West African facial features. There may even be other physical features that are less clearly racialized in the U.S.—such as height—that correlate with ancestry.
These physical features matter since they bring us back to square one. We cannot ultimately separate the more context-independent biological effects from genetic effects that interact with the social system, such as when lighter skin is rewarded. It could be that cognitive differences are genetically based, but the mechanism linking genes to IQ acts through social pathways (i.e., response to skin tone) rather than biological ones (i.e., brain structure). The darker-skinned sibling may get harassed by the police more often or get treated as less intelligent by his teachers (or parents for that matter) and this can, in turn, have real consequences for cognitive development. In other words, even if genes predict racial differences in IQ, they could do so because genes are good predictors of racial identification and treatment in society.
There has long been evidence—dating back to the days of W.E.B. Du Bois—that there is a pigmentocracy within U.S. black (and white and Latino) communities. More recent work has shown that this is not a uniquely American phenomenon but extends to Brazil, South Africa, and other nations with a creole, mixed population. We could try to measure skin tone and factor that out. But we cannot ultimately measure all the myriad cues about racial identity that we react to, especially since we may not even be aware of them. It could even be the case that African or European ancestry predicts height and that taller people are treated better in school, get more nutritional resources at home, and so on. Even though we do not generally think of height as a key dividing line for race, it does not mean that it is not silently associated—at the genotypic level—with the alleles that also differ by race.
The near impossibility of a definitive, scientific approach to interrogating genes, race, and IQ stands in contrast to the loose claims of pundits or scholars who assert that there is a genetic explanation for the black-white test score gap. That said, the consideration of genetics in racial analysis is not always pernicious. The ability to control for genotype actually places the effects of social processes, like discrimination, in starker relief. Once you eliminate the claim that there are biological or genetic differences between populations by controlling them away, we can show more clearly the importance of environmental (non-genetic) processes such as structural racism.
As genetic data become more available to the population, the mismatch between race and genetic ancestry (continental and subcontinental) should lead to a revision of racial discourse. When many whites realize that they have African ancestry and many blacks discover their European ethnic origins through DNA testing, the one-drop rule might crumble and racial dichotomies could soften into more complicated nuances of admixture. On the other hand, as the sociologist Ann Morning has argued, “even with a familiarity with racial mixture that led us to put categories like ‘quadroon’ and ‘octoroon’ on 19th-century censuses, the one-drop rule hardly crumbled. In fact, it was reinforced in reaction to that awareness.” It may be that scientific knowledge has more power and authority to complicate matters than firsthand, intimate knowledge of racial mixing did. But it may not. Either way—as in the cases of marital sorting, class mobility, and fertility—social genomics reveals hidden dynamics of race that belie our intuitions. We cannot be afraid to look.
Dalton Conley is the Henry Putnam University Professor of Sociology at Princeton University. His many books include Parentology: Everything You Wanted to Know About the Science of Raising Children but Were Too Afraid to Ask. He lives in New York City.
Jason Fletcher is Professor of Public Affairs, Sociology, Agricultural & Applied Economics, and Population Health Sciences at the University of Wisconsin-Madison. He lives in Madison.
1. Zea mays. Ensembl Gramene www.ensembl.gramene.org.
2. Weight, M.D. & Harpending, H. Some uses of models of quantitative genetic selection in social science. Journal of Biosocial Science 49, 15-30 (2017).
3. Hawks, J., Wang, E.T., Cochran, G.M., Harpending, H.C., & Moyzis, R.K. Recent acceleration of human adaptive evolution. Proceedings of the National Academy of Sciences 104, 20753-20758 (2007).
4. Even genetic assortative mating could cause genetic differences of significant magnitudes if it were prevalent enough; however, these would likely result in within-society cleavages. See, for example, Harpending, H. & Cochran, G. “Assortative mating, class, and caste.” The Evolution of Sexuality Springer, New York (2015).
5. Milot, E., et al. Evidence for evolution in response to natural selection in a contemporary human population. Proceedings of the National Academy of Sciences 108, 17040-17045 (2011).
6. This mistake is similar to partisan differences in attributing success in life to luck (genetic drift) versus effort and ability (natural selection). See Frank, R.H. Success and Luck: Good Fortune and the Myth of Meritocracy Princeton University Press, Princeton, NJ (2016).
7. Bogin, B. & Varela-Silva, M.I. Leg length, body proportion, and health: A review with a note on beauty. International Journal of Environmental Research and Public Health 7, 1047–1075 (2010).
8. Zuidhof, M.J., Schneider, B.L., Carney, V.L., Korver, D.R., & Robinson, F.E. Growth, efficiency, and yield of commercial broilers from 1957, 1978, and 2005. Poultry Science 93, 2970–2982 (2014).
9. These changes cannot even be attributed to selective migration—in which the genetically advantaged flock to areas that are flourishing—like the story of China’s rise perhaps can; Shanghai now attains a level of income equal to Italy whereas rural western areas are more like some African countries.
Excerpted from The Genome Factor: What the Social Genomics Revolution Reveals about Ourselves, Our History, and the Future by Dalton Conley and Jason Fletcher. Copyright © 2017 by Princeton University Press. Reprinted by permission.