Still Searching for a Justification: More Thoughts on Harden’s The Genetic Lottery

In addition to the usual disclaimers (i.e., this is an unpolished blog, written perhaps a bit more stream of consciousness and repetitive than some (all?) readers would like because this is a free time activity to which I am not devoting time to edit because I have football to watch), I will add one more. This turned out longer than usual. Brevity has never been my strong suit. Warning: unpolished and meandering.

At this point, I would guess that Harden’s book The Genetic Lottery, a rapid review of which was the focus of my last blog post, has been a success in terms of sales and stimulating thought and attention. I’m not a fan at all, and I’m still thinking about it. Yet, in terms of its actual contribution–in its logic and argumentation–I remain utterly perplexed by the plaudits the book has received. I have been thinking (and now writing) more about the issue I raised in my previous review about Harden’s claim that incorporating genetics has much to offer social science and policy, so much so that it is not just helpful but necessary to include genetics in social science models. I noted toward the end of my rapid review: “Given that Harden agrees that genetic engineering is unwise, what, exactly, does she think this [the incorporation of genetics into policy] offers us? She doesn’t tell us in this book.

The (lack of) answer to this question has continued to nag me, and so too for the value for (social) science understanding. Thus, I re-read—well, more like skimmed–the book and reviewed some other relevant works to try to smack myself in the face with their arguments for ‘why this is valuable’, so valuable, to remind the reader, that Harden avers that ignoring genetics in social science research and models is the moral equivalent of bank robbery [again, I think that she meant to use a burglary as an example, but still].

Here, I wanted to quickly outline what I understand to be their arguments for the value-added, even necessity, of incorporating genetics into research on human social behaviors/social science. In so doing, I aim to clarify what I see as the problems with her/their logic. First, I discuss social science and then policy.

Why incorporating genetics into social science models is valuable, even necessary: Harden and colleagues’ justification; (reader please note this my summarizing what I understand to be their arguments):

(1) All complex social behaviors are heritable. As Harden (2021) notes, twin studies have demonstrated for decades that for all complex social behaviors of interest to social scientists, heritability is substantial (an average of 50% heritability).

(2) Heritability estimates indicate causal effects of genetic differences on individual differences in traits. [Again, this is a contested viewpoint, but this is her view.]

(3) Ergo, individual differences in all complex social traits are partially caused by genetic differences, and, as Harden (2021) notes, we have known this for years. [At least twin studies showing non-trivial heritability of complex social traits have existed for years.]

(4) When examining the influence on social forces on complex social outcomes and behaviors (e.g., educational attainment, crime), leaving out genetic differences is a problem of omitted variable bias. That is, if we do not incorporate genetic differences, which may partly cause—only partly because it should be remembered for most outcomes the twin study heritability is <70% and for many reasons this is a high end estimate—putative environmental causes, these uncontrolled genetic influences can and will masquerade as causal environmental effects.

(5) Consequently, the estimate of the environmental effect will be less precise (and potentially inflated in some cases) by not parsing out genetic influences.

(6) Therefore, to get more precise point estimates of environmental influences, we must incorporate genetic influences.

(7) Harden et al. recognize that methods that can provide (roughly) genetically unconfounded estimates exist as instrumental variable methods and fixed effects models where individual differences are held constant to assess change over time in response to changing circumstances, but these require expensive panel data.

For the non-quantitatively oriented science reader, I will note a few things. First, to point #7, federally funded rich panel data already exist, and using such data, numerous fixed effects models have shown that changes in environments produce changes in the things that we care about. Second, and more importantly, precise point estimates are generally not of major interest to social scientists. Nearly all of our measures, including our outcome measures, are noisy, (contain error), even biased. In general, what we want to know is whether more of something (education, parental support) is associated with more (or less) of something else (income, education) that we care about, ideally with some theoretical orientation. Frequently the scale used to measure social influences is somewhat arbitrary anyway, such that the precise point estimate (e.g., weeks of schooling) associated with 1 point increase in the ‘social support scale’ is inherently vague. 

Third, for reasons that are out of scope, genetic measures (as PGS scores) are always noisy and biased as well, due to the measurement of only some of genetic variants we possess, imputation (informed guessing) for some of the unmeasured variants, and the presence of environmental confounding, known as population stratification, which can be understood more simply as the effects of shared culture or social structures in the form of distant relatedness. That is, people who live in geographically proximate areas and thus share more similar physical and social environments also tend to mate with each other creating greater genetic similarity in groups which also share more similar social and physical environments. Controls for population structure are included, but except in the case of sibling different studies, these are inadequate. 

PGSs created from the estimates from sibling studies are the rare exception, such that most PGSs are tainted with population confounding (i.e., pick up sociocultural and physical environmental differences). Therefore, PGSs capture both ‘genetic’ differences that influence the trait through biological mechanisms (usually distantly) and sociocultural differences that are associated with allele (genetic variant) frequency differences across subgroups. For a quick example, due to the greater UV rates at lower latitudes, if we were to do a GWAS of the Eastern US population for skin cancer, we would likely pick up, in addition to any genetic predispositions to skin cancer (e.g., genes involved in cellular repair) genetic variant (allele) frequency differences among those in the US South and those in the Northeast due to the fact that people in the South have tended to mate with each other and are more closely related and so too for the North. Some unknown number of these genetic differences, however, will have nothing to do with the biology of skin cancer and everything to do with being randomly differentially distributed between the South and North, the former which is exposed to higher UV rays and more sun. (These random differences that develop over time are known as genetic drift through assortative mating based on sociocultural and physical environmental proximity.) In short, some of the genetic variants identified will be a function of random genetic differences and associated with the outcome for purely environmental reasons that have nothing (biologically) to do with the outcome.

For all of these reasons, the ‘greater precision in estimates of the environment’, at the current moment, is debatable. Perhaps we’ll see a little greater precision in some environments, but a very meager and not very useful benefit. Thus, leaving out genetics is, in my view, akin to jaywalking (at worst) not bank robbery.

Why incorporating genetics into social science models is important for policy—Harden et al.’s view:

I must first admit I found this even less clearly articulated in Harden’s book, which is why I wrote that ‘she doesn’t tell us why in this book’. I don’t think she does, clearly. However, if one looks at some of her other co-authored work, especially with Koellinger (who she references as a high-quality cook in her book), one can see more clearly their ‘logic’. 

For example, in a paper called, “Genetic Fortune: Winning or Losing Education, Income, and Health”—similar to the ‘lottery’ with a somewhat awkward subheading (what does ‘losing education mean’?) a study/paper designed and overseen by Koellinger and co-authored by Harden and published online in November 2020 (though I have the updated December 2020 version), spells out why they believe this work is important to policy. I disagree with this reasoning, as you can imagine. Notably all of the below are quotes from Kweon, Burik, Linnér, Vlaming, Okbay, Martshenko, Harden, DiPrete, and Koellinger (2020), unless otherwise noted.[1]

(1) “The origins, extent and consequences of income inequalities” differ across contexts,”

(2) “a universal fact is that parents influence the starting-points of their children by providing them with family-specific environments and by passing down a part of their genes [1 of each chromosome from each parent, plus an X from mom and an X/Y from dad, all going well]. This phenomenon creates individual-specific social and genetic endowments that are due to luck in the sense that they are exogenously given rather than the result of one’s own actions [here we can see the luck language].”

(3) “Thus inequalities of opportunity can partly arise from the outcomes of two family specific “lotteries” that take place during conception—a “social lottery” that determines who are parents are [?social status], and a “genetic lottery” that determines which part of their genomes our parents pass on to us.”

(4) “Inequalities in opportunity restrict the extent of intergenerational social mobility and limit how much credit people can claim for achievements such as their education or income.” [Okay, inequalities in opportunity affect a lot of things, curious that these are the two accentuated here.”]

(5) **Key** “The relative importance of social and genetic luck has policy relevance because the extent to which people are willing to tolerate or endorse inequality partially depends on whether they perceive that disparity originates from differences in effort and choice (e.g., working hard) or from differences in circumstances that are outside of one’s control (e.g., luck in the social or genetic lotteries). The empirical results suggest that inequality that can ultimately be traced back to luck may be perceived as unfair and people may favor redistributive polices more strongly *if* inequality is the result of luck rather than agency” (bold and asterisk emphasis added).

Phrased alternatively, their argument here is that the more people perceive that disparate outcomes/inequalities are due more to luck than to personal agency/hard work, they may be more inclined to favor redistributive policies. (The word perception jumps out at me here; I will return to that later.)

(6) “*If* the outcomes of the genetic or social lottery influence economic outcomes, it [confusing pronoun usage] can challenge common intuitions about the relative importance of luck and agency” (asterisk emphasis added).

(7) “It is important for science and policy to understand the extent to which genetic and social fortune[s] contribute to inequality, the mechanisms that are at work, and whether and how the consequences of exogenously given endowments can be altered.”

This argument pulls in some new facets and combines them with the ongoing logic. Understanding “the extent to which genes and social fortune contribute to inequality” is important, they argue, because presumably that shapes people’s perceptions about the importance of such factors and therefore their willingness to support redistributive policies. Here they also add in a focus on mechanisms and changeability, presumably due to their obvious policy relevance-but genetics isn’t needed to examine changeability.

Therefore, the Kweon et al. (2020) paper “makes progress in this regard by using large-scale molecular genetic and family data to test the influence of genetic and family-specific endowments on income inequality and its consequences for health.” Health, you say; where did that come from? I agree; (for those not in the know, the funding for health outcomes in the USA from NIH is high, less so for non-health social outcomes.)

   A few points, of course.

 First, I must make note of the importance of the perceptions bit. Of course, facts and empirical patterns don’t determine action. Whether such facts are known and how they are interpreted/given meaning shapes action. Again, Harden and colleagues note that to the extent that people perceive that inequalities are the result of luck (genetic or social), the more inclined they tend to be to support redistributive policies. This makes sense. 

However, I have a few issues. First, the extent to which people’s perceptions of the sources of inequality are reflected by empirical evidence/facts is not entirely clear. Indeed, I am sure that a twin heritability study would likely reveal that a non-trivial portion of the variance in perceptions of sources of inequality would be found to be heritable. To be clear, from that finding, I do not personally conclude that this means that this same portion of variance across individuals is caused by genetic differences, given the inflationary biases of twin study heritability estimates. My point is, by their own logic, much of this variance in perception in the source of inequality is due to, even caused by, genetic differences. There is, in a sense, an infinite regress or circle in behavior genetic models when everything is ~50% heritable—perceptions, beliefs, attitudes, traits, and behaviors; every non-randomly assigned allegedly ‘environment exposure’ is approximately half caused by genetics, on this view, which makes everything a bit awkward.

Second, and more importantly, we already know both from common sense and a wealth of social research that both one’s family-specific environment (income, wealth, status, race/ethnicity, religion, beliefs) and genetic endowment shape one’s life trajectory, including social outcomes like educational attainment and income. We know this from a wealth of social science and behavioral genetic research and basic observation of reality. Harden tells us this repeatedly in her book and Kweon et al (2020) mention it in their paper.[2] WE KNOW THIS. Thus, there repeating the *if* this matters, then so and so, is a misrepresentation of the literature. We already know these matter. We do not need yet another study to show that these things matter, and it is somewhat disingenuous to highlight that these things matter, you all, so much so that if you exclude them from your models you are the moral equivalent of a bank robber, while turning around and publishing papers questioning whether these things matter. At least, that’s my opinion.

Third, social and genetic endowments are inextricable. We also know this. We are not going to be able to parse them out because human development and behaviors emerge from a biological system that always operates in with responses to social environments. Humans are organisms, which are processes in constant flux in response to internal and external input. Environments up and down regulate genes; initiate cascades of action and reaction; shape our motivations, desires, and behaviors, among other things. Likewise, our genetic differences can shape both the amount and the nature of protein products produced and other gene products in a manner that can and does affect how we look, perceive the world, and react to it. 

All of this is why the results of their study: “We show that the well-known gradient between sociogenomics status and health is partly rooted in exogenously given genetic and social endowments. Furthermore, we demonstrate that a substantial part of genetic luck for income and its link with health appears to operate via educational attainment and its accompaniments, i.e., environmental factors that are in principle malleable through policy interventions” can be met with a “duh”. Of course, this is the case. How this advances policy relevant knowledge one iota I cannot say (because I do not think it does).

Heritability says nothing about malleability, as Harden and Kweon et al. remind us on multiple occasions, and a wealth of social scientific evidence on traits that have been found to be substantially heritable has already shown that highly heritability says nothing about responsivity to social influences. Indeed, that is part of their argument—that genetic causes operate through malleable environmental pathways. But here, they throw “does it matter” as unknown and then answer it as if they are offering something new. That’s double dipping, which is kind of like jaywalking but dirtier.

Broadening our lens, and thinking about the well-known fact (again repeated by Harden in her book several times) that high heritability, interpreted by her to mean and thus include ‘genetic causes’, of differences in social outcomes say nothing about malleability to policy influences, brings to stark relief the question of why then do we care about the extent to which these differences may be partially—as again even the upward bounds of heritability are almost always less than 70%–rooted in genetic differences between people? Given that this is not relevant to changeability, I am left to believe that this is meant to go back to “perceptions”, and with it that is intended as the policy-relevant import of this work, in Harden’s view, and indeed, perhaps the purpose of her book.

Phrased more clearly, this would make the aim of Harden’s book, in my view to try to change people’s perceptions about the causes of inequalities from personal responsibility and hard work to ‘luck’, with an emphasis on genetics. Doing so, in her mind, will perhaps promote the redistributive policies she clearly publicly supports. 

This angle is also how she distances herself from the ‘bad’ (according to Harden: eugenic, racist) arguments of infamous hereditarian scholars before her—the Bell Curve types who, it might be noted, focus less on genetic differences, in general, and more on IQ, which they view as largely genetic and, crucially, mostly fixed, if not at birth, then certainly after childhood. Harden, for her part, recognizes that genetic differences do not imply fixity (although she has used the language of ‘genetic predisposition’, so this is in some ways a difference in degree rather than kind, but a notable one nonetheless). However, that recognition does not, as Harden argues, somehow make a consideration of genetics useful for social science or policy. From the fact that genetic differences do matter for development and individual social behaviors, it does not follow that incorporating (noisy, environmentally confounded) measures of genetic differences will advance social science models or policy since, as we have noted ad nauseam, heritable or genetic does not mean unchangeable. Whether I’m naturally a bad singer or fail to get the proper socialization about singing from my parents is irrelevant to the question of whether or not singing lessons (or parenting lessons for singing support) can make me a better singer. If they can work for me, we do not need to know the extent to which genetic and social endowments shape the extent to which I am a bad singer. That is, if we can teach or support parenting skills to make me a better singer, who cares about the why especially given that we cannot really answer this question anyway given gene-environment inextricability and context-specificity (though replace singer with student, since we don’t care about my singing…well, you might if you had to listen to it. I’m serious.)

In addition to being irrelevant to policy, there remains a potential dark side to even benign, explicitly anti-eugenic work and not only if these results are used by those with whom we disagree (e.g., the billionaire insurance person with whom Harden and colleagues had dinner with at the fancy French restaurant). Indeed, even work with ‘good intentions’ from Harden and colleagues to understand the sources of inequalities can reveal the potential harmful effects of genetically-informed policies.

Specifically, in co-authored work, Harden focuses using PGSs as a molecular tracer in school achievement. Although more detail is out of scope, for reasons abovementioned, including but not limited to their environmental confounding, PGSs do not measure genetic potential for educational attainment—they capture the differences in those who receive educational attainment under current systems. And again, potential for educational attainment does not reside in our genomes, but emerges from a complex biosocial system in which genes are important resources but not the drivers of development. Yet, that is often missed or ignored despite the professed environmental awareness of those conducting this work. 

Additionally, Harden et al recognize that PGSs are not useful for individual prediction but that they are useful for aggregate prediction and can be used, for example, to assess school performances. They suggest that we might, for example, control for the average PGS of schools when comparing their performances, and/or devote extra resources to schools with more students with lower ‘education-related genetic variants’. However, this quite clearly, in my view, begins to solidify this view of these PGSs/measures of ‘education related genetic differences’ as “education potential”, which is problematic. And while the outcome might be positive in some cases, even if misguided, e.g., by directing resources at the lower SES schools, given the environmental confounding, there are other potential negatives, including labeling and lower expectations. 

Equally important, why in the world would we use noisy, problematic measure of ‘genetic potentials’ to direct resources and evaluate schools, rather than more easily measurable and more accurately predictive measures of past achievement, SES, and even standardized test scores? As others have noted, a much better predictor of future school performance is past and current performance (see Morris et al. 2020). We can easily see which students struggle and ascertain which students are getting support and extra help in the home and which students aren’t and respond accordingly with more sensitivity and specificity. No need for genetics whatsoever.

Genetic measures are not only less accurate predictors but also potentially a source of differential treatment. Sure, Harden wants this information to be used to good ends, but why in the world do we think that it will be? Best intentions gone awry is perhaps the most obvious lesson from all of history, and there is no reason to think that many actors agree with us on the proper courses of action. Other potential implications could be lowering expectations and standards for schools/individuals with lower ‘education-related genetics’ (estimates). One could easily see how we could treat such measures as potential, think this is the best we can get from individuals, and set the bar low for them, despite the fact that, to repeat ad nausem, even if educational attainment is strongly genetically influenced, it is strongly socially influenced and–both genetic and social influences are potentially malleable. 

In sum, the policy value of this work for education systems is, in my view, minimal to nonexistent and potentially harmful to students and society. I might also note that almost all of the samples used to create these large-scale education-related (and, income-associated) “genetic propensities” use older samples, who grew up in the pre-internet era. One of the younger samples is the Add Health sample, which includes my age category (I’m 42), when google, youtube, and other concomitants of the growth of non-dial-up internet access were not prevalent (at least not until I was in graduate school). Today’s students grow up in a connected world of easily accessible information online. These technological innovations have transformed the learning environment in non-trivial ways, further altered by the pandemic. Does anyone want to argue that the individual characteristics shaping educational achievement and income are the same today as they were for children born in the 1970s and early 80s, much less the 1940s-1960s? I don’t; (even as I would agree many are the same). Distractibility working on a computer is, in my view, exponentially greater than that in pre-internet times when we worked with pen and papers and with books (hard copies of). 

In sum, for real this time, even if genetic differences have a substantial influence on educational attainment, income, and via those pathways, health outcomes, given that these social influences are malleable regardless of their origin, there is no obvious policy-relevant value added to incorporating genetic differences given our measurement and knowledge limitations. If genetic meant unchangeable, then a case could be made; but it doesn’t. There are potential harms. For all these reasons, I find these arguments to be flimsy at best, with some of the recent framing about uncertainties (*if* this is shaped by social and genetic endowments), which have been well established, as unknowns, almost disingenuous. 

One can believe that genetic differences exist and shape differences in complex human social outcomes without being a eugenicist or racist or sexist, etc. But it does not follow that study of the effect of genetic differences on these social outcomes from an anti-eugenicist or anti-racist perspective is thereby useful and important (or that it can’t then be used to support racist or eugenics ideologies and policies, to be fair, a fact recognized by Harden and others on multiple occasions very clearly. Clearly recognizing a danger and acting to prevent it, are, however, two different things, which is how I once broke both my hands.).

If you made it this far, bless you, ha. Before closing, I want to reiterate what this long-winded verbosity was and wasn’t about. I am *not* arguing that perceptions about the sources of inequality do not matter for how we address (or whether we tolerate) inequality. I agree that perceptions about the sources of inequalities shape individuals’ views about whether and how to address inequalities. I am saying that we have a wealth of research over decades that shows that genetic and social endowments at birth profoundly shape our economic and social outcomes. We do not need more data showing this if the aim is to change perceptions; we do not need genetic data, for example, to show more clearly that environments matter for our life trajectories. Doing more research to compile yet more facts that this matters is not, in my view, necessary or efficient to change perceptions, in other words, if that is the goal.

To summarize too my thoughts on policy-relevance, my argument is not that genetics don’t matter or that genetic data can’t tell us anything. To use again Harden’s example about controlling for average student PGSs for educational attainment in schools to assess school performance while controlling for individual differences, this is both unnecessary and limiting. Net of environmental and shared family environments, the educational attainment PGS explains not quite 3% of the variance in education. And without controlling for such confounding these PGSs explain 12-14% of the variance in educational attainment. Why would we control for a noisy measure that explains less than 15% of the variance, when we could use already available standardized test scores from previous years or past school performance–scores already available–that would explain more than 50% of the variance in student performance. The only reason that I can think we would do that is if we assume that the genetics measure is actually a measure of ‘genetic potential’ or ‘ability’, an assumption which Harden et al. disavow. This doesn’t mean genetic differences don’t matter. It’s like bringing pliers for a wall nailing job; sure you can do it, but why would you when you could bring and use a hammer.

Perhaps I’ll read the book one more time in my “for fun” time to make sure I haven’t missed anything. Feel free to add your thoughts; if I’ve missed something important, I’d particularly like to hear about it.

[1] Citing from Harden’s book required much more words as she sprinkled arguments in larger discussions with examples and personal stories, which is good for a trade book, but makes for more difficult quoting. However, she makes similar claims. For example, Harden (2021, pp.181-182) makes: “First, environmental experiences—whether it be having a sexual relationship at a certain point in one’s adolescence or receiving a certain type of parenting or living in a certain type of neighborhood—can be correlated with life outcomes but not be causes of them. Second, policies that are built on a flawed understanding of which environments are truly causal are wasteful and potentially harmful [why–since malleability is not related to heritability?]…. Third, genetic data—whether it be comparisons of identical twins or comparisons of people with similar polygenic indices— help researchers solve the first problem and, in so doing, avoid the second problem. Genetic data gets one source of human differences out of the way, so that the environment is easier to see.” 

[2] Curiously, in what is likely a common instantiation of our arbitrary citing practices and unclear protocols and expectations, Kweon et al. (2020) cite Rietveld et al. (2013) twice in one paragraph on the bottom of p.5 cite after a statement about what twin studies show. Yet, Rietveld et al. (2013) is a GWAS study–known as EA1 (educational attainment GWAS 1). I’m not sure if they cite Rietveld et al. because Rietveld et al. also noted what twin studies show, but that is confusing, in my view. When someone (perhaps most commonly the author in their prior work) make a similar statement about existing research, this does not not warrant citing the prior research for making that not-so-unique claim. If wanting to point to a similar paper–in this case no idea why the Rietveld et al. was chosen, I think more helpful to say “see summary in xx”. Just me, perhaps.

Genetic Promissory Note with a Moral Twist

A Rapid Book Review[1] of The Genetic Lottery by Kathryn Paige Harden (Princeton University Press)

We all know that our DNA makes us different and unique. To what extent, how, and whether we can understand how our genetic differences shape differences in social and behavioral outcomes has long been debated. [Post posting read–that is a terrible sentence.] The field known as behavior genetics has used family, twin, and adoption studies, and more recently measured genetic differences, to show that our genetic differences are correlated with social and behavioral outcomes that matter to us. The idea that ‘our genes’ shape our social and behavioral outcomes, including educational attainment, dates back at least 50 years.

In her forthcoming work, K. Paige Harden, a now-renowned behavior geneticist at the University of Texas at Austin, draws on these findings to a make a stronger (more controversial) case. Skirting important methodological issues, Harden argues that these studies identify genetic causes of our life outcomes, such as educational attainment, income, wealth, and ‘externalizing’ behaviors (crime, substance use, risky sex). Further, she claims that social science research and policy must incorporate a consideration of genetic differences into our theories, models, and policies if we are to truly understand inequality and reduce it. By positioning herself as distinct from those who are infamous for promoting genetic determinist claims, especially with direct or indirect implications for genetic racial differences in outcomes like IQ, Harden frames herself as a scientific realist with progressive aims. Yet, as I will quickly argue here, the reasonable, progressive story she presents only works by ignoring or downplaying important scientific details. 

Having just finished reading her book, I feel compelled to write something in response, in part because Harden’s writing is engaging, disarming, and persuasive and likely appeals to the segment of the public who hear of the irrational academics who deny biology (e.g., recognition of the reality of biological sex in gender studies) along with those who wish to position themselves against those Galtonian types and Bell Curve supporters of the world, whose works are fodder for white supremacist groups, according to Harden. (She makes several claims that white supremacists are avid consumers of the scientific products of these scholars; I have no idea if that is true). In large part, Harden’s book continues her (and others’) appeal to use genetics because those other (‘bad’) guys will use it anyway and not to good ends. Yet, Harden’s clear prose and ostensibly lucid arguments obscure substantial scientific complexities and unknowns, and contains some leaps in logic and reasoning. With few minutes I have, here are my thoughts hastily written. 

If you are looking for a detailed overview or a description of the biological and methods of contemporary social science genomics (sociogenomics) work, including GWAS, polygenic score studies, sibling difference studies, and the like, look elsewhere. Introducing readers to the science of sociogenomics is not the aim of this book. Indeed, for readers like myself with extensive familiarity with sociogenomics, including Harden’s prior works, this book’s primary new contribution is its (a) depiction of her conception of causality, and (b) a glimpse into her personal life through stories. For those not reading her recent work in which she pitches many of these same arguments (including a 2021 Annual Review of Psychology piece, for the interested reader with less time), Harden does flesh out the arguments that she presents in recent work elsewhere, captured in the summary of the primary aim of her book:

“I am going to argue that [the data showing the] relationship between measured genes and educational outcomes, is also critically important, both empirically and morally, to understanding social inequality. Like being born to a rich or poor family, being born with a certain set of genetic variants is a lottery of birth…. And, like social class, the outcome of the genetic lottery is a systemic force that matters for who gets more, and who gets less, of nearly everything we care about in society” (14-15). 

Harden argues, incorrectly in my view, that the genetic influences on social outcomes, like educational attainment, are not given due attention in social science and policies in part due to our sordid legacy of eugenics, which she immediately addresses head on and from which she distances herself. As a result of this history, in Harden’s view, mainstream social science is ‘biophobic left’, such that it theorizes ‘genetic sameness’ out of fear of what studying genetics might reveal about ourselves and how this may be put to use (in the service of bolstering the status quo and social hierarchies). I will note, and do so more below, I do not think this is a proper characterization of the position of most who critique behavior genetics.

On the other side, Harden argues that there are others who support genetics research on social outcomes, include a eugenics right, which has and will put this to use in the service of inferiorizing racial/ethnic and other disadvantaged groups. Harden positions herself as occupying the rational (ostensibly non-ideological) middle: In contrast to this ‘eugenics view’, Harden states that “[w]hat I am aiming to do in this book is to re-envision the relationship between genetic science and equality.” She asks, “[c]an we peel apart human behavioral genetics … from the racist, classist, and eugenicist ideologies it has been entwined with for decades? Can we imagine a new synthesis? And can this synthesis broaden our understanding of what equality looks like and how to achieve it?” (p18-9).

To this she answers not just ‘yes we can’, but ‘we must’. Indeed, in a surprisingly aggressive section of the book, which departs someone from her tone elsewhere, she argues that to do social research without considering genetic differences between individuals is the moral equivalent not of jaywalking but bank robbery(!!). Specifically, Harden writes about an asserted (but not demonstrated) “tacit collusion in social science to ignore genetic differences between people.” She states such ‘tacit collusion’ (which I dispute exists, more on that below), “is not wrong in the way that jaywalking is wrong…. It’s wrong in the way that robbing banks is wrong. It’s stealing.” 

Yikes. For the non-criminology readers, robbery isn’t ‘stealing’. Robbery is the use of force or threat of the use of force to take something from others; in bank robbery, this would be money. Perhaps if she mentioned this offhand or in a talk, I may let it go, but in a book this was clearly a thoughtful, albeit absurd and unjustified in my view, moral comparison. How does she get here? And, are her arguments sound? [Foreshadowing: no idea and no.]

The journey is interesting, especially with the relatable personal examples, but the logic and evidence presented is partial and tendentious. Harden battles with straw men, overlooks nuance and contrary or complicating evidence, and deftly avoids several of the longstanding critiques of behavior genetics, which now apply to sociogenomics: these include the population specificity and, therefore, incomparability of heritability studies across groups (defined, for example, by social class), the social construction of the outcomes, and downward causation, as well as a host of methodological issues, including assumptions and limitations, in current GWAS and other sociogenomics studies.

 I do think there is much to discuss on these issues (in fact, I’m writing a book about it myself), but charitable engagement with different views and thorough engagement with existing scientific evidence and theory is not found in this book, in my reading. She’s selling a view, in part by curiously denigrating her opponents while ignoring their critiques. I’ll briefly break down the arguments into their two parts to reveal the shortcomings. 

First, Harden’s portrayal of the genetic-resistant, even biophobic, mainstream social science is misguided, in my view. Few to zero social scientists believe endorse a ‘genetic sameness’ or ‘blank slatist’ view of the world, where individuals are genetically the same, and no scholar I’ve ever met. While her book is thin on citations, for a university press book, these sections are particularly sparse in terms of actual references. Rather than scholars, Harden references speeches and claims made by non-scientist, then president Bill Clinton on the Human Genome Project in support of her arguments for the mainstream social scientist view of ‘genetic sameness’. This straw man depiction allows Harden to dismiss social scientific critiques as being ideological rather than scientific—and no doubt some are ideological. But others are scientific. These are curiously ignored or quickly dismissed without engagement. 

Harden also repeats the longstanding argument that social science genomics continues to be relegated to the margins of academia and ignored by social scientists. Yet, here too, the evidence is missing, and I disagree. Harden has received considerable public and private funding, including prestigious fellowship, like several of her sociogenomics and behavior genetic colleagues. She, like those colleagues, publishes in high prestige general science outlets and social science outlets. Sociogenomics work receives public and media fanfare that I would argue is significantly greater than that of most social scientific work. The claim that the public and academics are tacitly colluding to ignore genetics is surely questionable (and requires supportive evidence) given that Harden herself has graced the pages of the NYT and New Yorker, as well as the Guardian, the Atlantic, and others, with these same arguments—with much fanfare–in addition to publishing these ideas in prestigious social science journals. Given sociogenomicists’ success in funding, publication, awards, and popularity—where exactly is the ‘tacit collusion’ to ignore this work? As Aaron Panofsky has argued, this claim that behavior genetics scholars scholars are outsiders fighting a reality-resistant academia is central to the identity of this field. Yet, at present, I keep coming back to ‘who does she think believes ‘genes don’t matter” because she doesn’t cite these people; (some personal correspondences where no one says ‘genes don’t matter’ are discussed). I think Harden’s creating an oversimplified, inaccurate portrait of critics on the political left is a result of her misunderstanding our critiques (which I turn to next).

Harden takes great pains to distance herself from the ‘eugenics’ or ‘Galtonian’ scholars, such as Robert Plomin, and the late Herrnstein as well as Charles Murray (of the Bell Curve infamy). Although at times I found myself concerned that she was exaggerating their differences, it seems clear that Harden truly believes that studying social science genetics is not just consistent with supporting egalitarianism, but it is necessary to creating a better society. Yet, why this is the case is never clearly articulated, in my reading. Importantly, in making this case for its importance (and the moral imperative that social scientists include genetics), Harden skips over some important methodological details and less supportive studies that would cast some doubt about her claims. 

For example, Harden notes that education polygenic scores explain from 10-14% in educational attainment (without noting this is basically net of only age and sex and 10 or so ancestry PCs). While mentioning that these findings ‘hold up’ when using sibling studies, which control for the potential environmental confounding variables by examining differences between siblings who share such environments, she never acknowledge that the variance explained/effect size drops in these sibling studies from 10-14% to <3%. Nor does she note that the variance explain dives when well-known, easily measurable variables like parental income and educational attainment, are included. Throughout she grapples with ‘genetics of educational attainment’ which, she claims, causally explains more than 10% of differences in educational attainment rather than the more realistic (net of relevant controls) relatively <3%.

This matters for her thesis. Given that ‘genetics’ explains less than 3% of the variance in educational attainment net of environmental confounds, it is (a) unlikely that it will explain away *larger* social environmental influences, such that we are being morally bankrupt (or rather bank robbers) for not included genetic measures in social scientific models, and (b) unlikely to significantly shape public policies in a way that would radically change things. That is not to say it can’t; some social scientific variables that are considered important explain less than 3% of the variance in outcomes. Yet, we have some idea what these variables are and what they do. This is not the case with current sociogenomics studies.

Harden also ignores concerns about what these GWAS results indicate. She barely mentions, more as a quick aside, that GWASs do not measure genes or causal variants, and that efforts at biological annotation (i.e., linking these measured genetic variants with genes, much less causal variants) remains an exercise in educated guesswork. She asserts that, for example, the ‘genes relevant to educational attainment are found in the brain’, while also recognizing elsewhere that because we, for example, treat taller, more attractive people better, they have advantages in educational and labor market outcomes which would, in her view, be appropriately deemed a genetic cause. That we still don’t know what most genes do is fully ignored in this book. The charge that scholars that fail to consider genetic influences are morally equivalent to bank robbers against this backdrop seems silly at best.

Ignoring Downward Causation

Harden devotes a section to causation to bolster her (quite controversial) claim that heritability studies identify genetic causes of individual differences. Curiously, she does not sufficiently engage with the work of her mentor who has written several pieces articulating why heritability studies are not about cause, (personally, I agree with her mentor Turkheimer on this one). Even more surprisingly, she uses the hypothetical from Sandy Jencks explaining how putative genetic causes reflect social causation and thus heritability studies cannot be used to inform us about biological causes. In Jencks’ well-known hypothetical, under an arbitrary social policy that banned red-haired people from getting an education, genetic differences related to (causing) red hair would appear as genetic causes of educational attainment, despite the cause actually being the social policy proscribing education for those individuals. This is really important to understand, as I believe this is a key source of differences in approach between scholars such as Harden and myself, and why behavior geneticists like Harden are speaking at not with behavior genetic critics.

The red hair example seems, on the one hand, preposterous because we obviously would never exclude people based on their hair color….but then you remember we excluded people on the basis of skin color and sex not very long ago. But, today, you say, this wouldn’t happen in western industrialized countries, even if in other parts of the world some biological characteristics (e.g., sex) do restrict people from education. What I and others have argued, and Harden does not fully account for, is the fact that our genes, and thus the effects of our genetic differences, always operate in context, and an unequal one at that. And, genetic studies—even sibling difference studies—do not control fully for context. As Harden recognizes, people who are more attractive tend to be treated better in a variety of social environments, including educational ones. But does anyone—besides Harden—really think we want to focus on genetic differences related to greater attractiveness as causing higher education? Whether or not this is properly treated as a ‘cause’ of educational attainment, how in the world is this useful to help (a) advance knowledge or (b) ameliorate inequality in a world where we can easily see who is more conventionally attractive and measure any privileges they may experience from it (see Monk, Esposito, & Lee 2021). Second, again, we do not know what most genes do (and, as Harden doesn’t really explain well, we don’t measure genes in GWASs, we measure variants). 

I, and others, have a serious problem with studies of the ‘genetic potential for educational attainment’ because they confuse downward causation with upward causation by viewing genes as the primary cause of action. The effect will be—as Harden admits openly—that social policies that give meaning to genetic differences that are otherwise not involved in the biology of educational attainment, will be conceptualized as ‘genetics of potential’ or ‘innate differences’, when they may result from social and physical arrangements. To use but one real world (non-red haired exclusion policy) example, many kids have a lot of energy and struggle with the artificial nature of the classrooms that require us to stay still and be quiet, much more so than the careers that we may choose and the lives we craft around them (e.g., use lunch break to go on a run)–because everyone must go to school, usually not of their choosing, but we have agency in the choice of our jobs (within huge constraints, of course). Yet, in a school district where recess and exercise is shortened or not daily (as I experienced in my third grade class when I struggled to ‘not talk so much’, where we had recess only on Mondays and I ended up in the principle’s office for talking too much), or in all schools where physical activity and movement breaks are arbitrarily restricted, those kids who have a higher metabolism or more energy—in many ways and contexts a positive trait—will be penalized, stigmatized (maybe as ADHD, when they just need to move more), and struggle. Do these kids have a lesser ‘genetic potential for educational attainment’? I would say no. Harden’s view would say yes. 

Aha, but you may argue, Harden thinks we need to understand these differences, identify these ‘high energy genes’, and accommodate those individuals!! That all sounds well and good, but a closer look suggests otherwise. Talk to a first-grade teacher (such as my sister), and you will find that within the first few days of class she can often readily identify the students who have excess energy and could benefit from (my words) ‘a good running’ (such as my own son). Second, recall the effects of these genetic variants are MINISCULE. There is no ‘high energy gene’ that we can find and figure out what it does, and again, we can usually already identify the high energy kids with ease by watching them for a day or two.

What Harden fails to acknowledge and grapple with is the fact that most teachers can readily identify students who struggle, and many teachers can understand the source of their struggles (focus versus logic, versus application of concepts, versus problem solving). In a recent piece, Morris et al. (2020) examined whether ‘education-related genetics’ could actually provide more useful information than well-established, easily measurable variables such as prior GPA, parental educational, current performance in shaping policies or programs to enhance educational attainment. They concluded, quite clearly, that genetics does not really move us forward in policy or programs or understanding.

Harden suggests that by incorporating genetics, we will have better interventions and waste less money, but how is that supposed to work? We have already identified low hanging fruit, in terms of large effect size genes for monogenic disorders. The genetic influences on educational attainment are nothing like that, instead characterized by thousands of variants associated with educational attainment for reasons we do not know and probably, for most, will never really understand (at least in the next several decades, if ever). Given that Harden agrees that genetic engineering is unwise, what, exactly, does she think this offers us? She doesn’t tell us in this book.

In sum, because my time is running out, Harden’s book is interesting, if oversimplified and unsatisfying. She exhorts us to incorporate genetics for a more egalitarian society, but does not tell us how this would enhance understanding or make society more equal. And, she rightly notes that resources are not unlimited, which is why I question our application of millions of public funding to the understanding of genetic influences on educational attainment when the payoff is unspecified.

Harden thinks the worst-case scenario is that we are going to find that some people are just ‘better at educational attainment’ which could be used to justify the status quo, which is why we have to study it with an egalitarian approach. I disagree. We already know some people are better at educational attainment, just like some people are better at golf, playing musical instruments, learning foreign languages, and dancing (not me). We aren’t all the same. However, education is not like height or deafness, two examples she uses frequently as analogies. Educational attainment is not a ‘biological trait’, except in the banal sense that everything we do is biological because we are biological creatures. Given the state of knowledge, we already know that genetic effects are far too complicated to link to such a distant, complex, socially constructed outcome like educational attainment. Instead, in my view, the realistic worst-case, is, as we have seen for the candidate gene era and candidate gene interaction era before it, that we throw tens of millions of dollars and hundreds of thousands of scientists hours chasing a chimera of actionable or useful genetic influences for social disparities. I’d rather throw that money at social interventions that may not work well, but they might help a few. Harden disagrees, which she is free to do, but I won’t call her a bank robber [the moral equivalent of] for thinking differently.

Back Cover Description of ‘The Genetic Lottery’

A provocative and timely case for how the science of genetics can help create a more just and equal society

In recent years, scientists like Kathryn Paige Harden have shown that DNA makes us different, in our personalities and in our health—and in ways that matter for educational and economic success in our current society.

In The Genetic Lottery, Harden introduces readers to the latest genetic science, dismantling dangerous ideas about racial superiority and challenging us to grapple with what equality really means in a world where people are born different. Weaving together personal stories with scientific evidence, Harden shows why our refusal to recognize the power of DNA perpetuates the myth of meritocracy, and argues that we must acknowledge the role of genetic luck if we are ever to create a fair society.

Reclaiming genetic science from the legacy of eugenics, this groundbreaking book offers a bold new vision of society where everyone thrives, regardless of how one fares in the genetic lottery.

[1] Because I’m busy, like everyone else, but I also have things I want to say about things, I allow myself ‘fun writing’ on topics that I feel compelled to write about, without encroaching upon my family/leisure time and/or my work time. So, I am giving myself 30 minutes write this review. These are quick thoughts written hastily because I want to and I can. I ran out of time to think of a catchy title, so this one, which is disappointing, will have to do.