In this final chapter, then, I hope to start the conversation about what it means for science and policy to be actively anti-eugenicist, by offering five general principles:
1. Stop wasting time, money, talent, and tools that could be used to improve people’s lives. 2. Use genetic information to improve opportunity, not classify people. 3. Use genetic information for equity, not exclusion. 4. Don’t mistake being lucky for being good. 4. Consider what you would do if you didn’t know who you would be.
For each of these principles, I will contrast three positions. First, the eugenic position positions genetic influence as a naturalizer of inequality. If social inequalities have genetic causes, then those inequalities are portrayed as the inevitable manifestations of a “natural” order. Genetic information about people can be used to slot them more effectively into that order. Second, the genome-blind position position sees genetic data as the enemy of social equality and so objects to any use of genetic information in social science and policy. Whenever possible, the genome-blind position seeks not to know: scientists ought not to study genetic differences or how they are linked to social inequalities, and other people in society ought not to use any scientific information that is generated for any practical purposes. These two positions can be contrasted with what I am proposing is an anti-eugenic position that does not discourage genetic knowledge but deliberately aims to use genetic science in ways that reduce inequalities in the distribution of freedoms, resources, and welfare. [...]
Stop Wasting Time, Money, Talent, and Tools
EUGENIC: Point to the existence of genetic influence to deny the possibility of intervening to improve people’s lives.
GENOME-BLIND: Ignore genetic differences even if it wastes resources and slows down science.
ANTI-EUGENIC: Use genetic data to accelerate the search for effective interventions that improve people’s lives and reduce inequality of outcome. [...]
Use Genetic Information to Improve Opportunity, Not Classify People
EUGENIC: Classify people into social roles or positions based on their genetics.
GENOME-BLIND: Pretend that all people have an equal likelihood of achieving all social roles or positions after taking into account their environment.
ANTI-EUGENIC: Use genetic data to maximize the real capabilities of people to achieve social roles and positions. [...]
Let’s go back to a specific example that I told you about in chapter 7, about the relationship between the educational attainment polygenic index and mathematics course-taking in high school. Students who had a higher polygenic index were more likely to be enrolled in geometry (versus algebra 1) in the ninth grade, which put them on track to complete calculus by the end of high school. Students who had a higher polygenic index were also less likely to drop out of math once it became optional. What can and should be done with that information?
The eugenic proposal would be to test students’ DNA and use it to assign them to mathematics tracks, such that students with low polygenic indices are excluded from opportunities to learn advanced mathematics. The gene-blind proposal would be to insist that the research connecting genetics and mathematics course taking shouldn’t have been done in the first place. The anti-eugenic proposal is to apply that genetic knowledge toward (a) understanding how teachers and schools can maximize the mathematics learning of their students, and (b) spotlighting how academic tracking entrenches inequalities between students.
Regarding the first goal, consider that one of the greatest challenges to understanding which teachers and schools are best serving the needs of students is that students with different learning needs are not randomly distributed across teachers and schools. A trenchant criticism of using standardized test scores as a metric for teacher and school “accountability”—that is, for identifying poorly performing teachers and schools—is that student test scores are highly correlated with student characteristics, such as family socioeconomic status, that precede the child’s entry to school and that are non-randomly clustered across schools. “Good” schools, defined as schools with high average test scores, are, in actuality, often better described as rich schools with high concentrations of affluent students. (A similar problem besieges identifying the best doctors and hospitals: the best doctor is not the one who avoids treating the sickest patients.)
Researchers have long recognized that estimating school effects on student academic outcomes is a tricky problem, and one can begin to make fair, “apples-to-apples” comparisons among schools only if one incorporates measures of student characteristics such as family background, previous levels of academic knowledge, etc. The appropriate question is not “How do students in school X fare differently than students in school Y?” because the students in school X could be already different from the students in school Y in ways other than the school they attend. The appropriate question is, “How would a particular student have fared differently if he had attended school X rather than school Y?” (Again, we see the importance of counterfactual reasoning for causal inference, as I explained in chapter 5).
In attempting to identify school effects, it is commonplace for researchers, educators, and policymakers to consider information about one accident of birth: a student’s socioeconomic status. But I and others have observed in our research that information from a student’s DNA, in the form of a polygenic index, also predicts academic outcomes, above and beyond information on family socioeconomic status. As I described above, this does not mean that we should use polygenic indices to classify students and restrict their opportunities to learn. It does mean, however, that we can evaluate how students who have equivalent polygenic indices fare differently in their outcomes when they attend different schools.
In one study of US high school students, we found that students with low education-related polygenic indices were, on average, less likely to continue in their mathematics education in high school. But their dropout rates differ substantially across school contexts. In schools that primarily serve students whose parents have high school diplomas, even students with low polygenic indices take a few years of math after the ninth grade. In fact, students with low polygenic indices in high-status schools fare about as well, in terms of their persistence in math, as students with average polygenic indices who attend low-status schools.
This finding is just barely scratching the surface. What, specifically, is happening in higher-status schools that keeps even students who are statistically likely to drop out of math from actually dropping out? How do you make the practices of such schools more widely available to all students? The path from basic research like this study to educational policy reform is long and tortuous.
But even though it is just a first step, this study is revealing a basic and important truth: given a certain fixed starting point in life—inheriting a certain combination of DNA variants—some people get much further in developing their capability to solve mathematical problems. These mathematical skills have lifelong benefits for an individual in terms of future education, participation in the labor force, and ease with navigating problems of everyday living. In fact, math literacy is so important for a student’s future that the opportunity to learn math has been called a civil right. Genetic data has thus revealed an inequality of environmental opportunity, one that calls out for redress.
Other environmental inequalities could be similarly diagnosed using genetic data. Which health interventions reach people who are currently most genetically at risk for poor outcomes? Which schools have the lowest rates of disciplinary problems among youth who are currently at most genetic risk for aggression, delinquency, or substance use problems? Which areas of the country are “opportunity zones,” where opportunity is defined not solely in terms of how children from low-income families fare, but also in terms of how children who are genetically at risk for school problems or mental health problems fare? If researchers embrace principle #1, and start embracing the possibilities of genetic data, we will have a wealth of new information to address these questions.
Use Genetic Information for Equity, Not Exclusion
EUGENIC: Use genetic information to exclude people from health care systems, insurance markets, etc.
GENOME-BLIND: Prohibit the use of genetic information per se but otherwise keep markets and systems the same.
ANTI-EUGENIC: Create health care, educational, housing, lending, and insurance systems where everyone is included, regardless of the outcome of the genetic lottery. [...]
Don’t Mistake Being Lucky for Being Good
EUGENIC: Point to genetic effects on intelligence as proof that some people naturally have more merit than others.
GENOME-BLIND: Accept the logic of meritocracy while ignoring the role of genetic luck in developing skills and behaviors that are perceived as meritorious.
ANTI-EUGENIC: Recognize genetics as a type of luck in life outcomes, undermining the meritocratic logic that people deserve their successes and failures on the basis of succeeding in school. [...]
Consider What You Would Do, If You Didn’t Know Who You Would Be
EUGENIC: The biologically superior are entitled to greater freedoms and resources.
GENOME-BLIND: Society should be structured as if everyone is exactly the same in their biology.
ANTI-EUGENIC: Society should be structured to work to the advantage of people who were least advantaged in the genetic lottery.
Facts are value-neutral. If you say e.g. “IQ exists”, will other people classify you as a good guy, or as a bad guy? If it’s predictably the latter, we won’t have enough “anti-eugenists”, because anyone non-autistic who cares about other people will be discouraged from studying IQ seriously.
What if the “least advantaged” e.g. dumb people actively want things that will hurt everyone (including the least advantaged people themselves, in long term)? Maybe the dumber they are, the more kids they want to have. Or maybe the dumber they are, the more they want to make decisions about scientific research. Should the biologically privileged respect them as equals (and e.g. let themselves get outvoted democratically), or should they say no?
Shortly, you can make it sound easy by ignoring how this stuff works in real world.
If you say e.g. “IQ exists”, will other people classify you as a good guy, or as a bad guy?
That’s not a criticism of Harden’s book though, right? I think she’s trying (among other things) to make it more socially acceptable to say that IQ exists.
Maybe the dumber they are, the more kids they want to have.
What if the “least advantaged” e.g. dumb people actively want things that will hurt everyone (including the least advantaged people themselves, in long term)? …Or maybe the dumber they are, the more they want to make decisions about scientific research. Should the biologically privileged respect them as equals (and e.g. let themselves get outvoted democratically), or should they say no?
I think that people of all IQs vote against their interests. I’m not even sure that the sign of the correlation is what you think it is; for example, intellectuals were disproportionately supportive of communism back in the day, even while Stalin and Mao were killing tens of millions. I’m sure you can think of many more such examples, which I won’t list right here in order to avoid getting into politics fights.
The answer to questions like “what if [group] wants [stupid thing]” is that various groups have always been wanting stupid things. We should just keep fighting the good fight to try to push things in a good direction on the margin. For example, I think prediction market legalization and normalization would be excellent, as would widespread truth-seeking AI tools, and of course plain old-fashioned “advocating for causes you believe in”, etc. If some people in society are unusually wise, then let them apply their wisdom towards crafting very effective advocacy for good causes, or towards making money and funding good things, etc.
And this whole thing is moot anyway, because I would be very surprised if the genetic makeup of any country changes more than infinitesimally (via differential fertility) before we get superintelligent AGIs making all the important decisions in the world. The idea of humans making important government and business decisions in a post-ASI world is every bit as absurd as the idea of moody 7-year-olds making important government and business decisions in today’s world. Like, you’re talking about small putative population correlations between fertility and other things. If those correlations are real at all, and if they’re robust across time and future cultural and societal and technological shifts etc., (these are very big and dubious “ifs”!), then we’re still talking about dynamics that will play out over many generations. You really think nothing is going to happen in the next century or two that makes your extrapolations inapplicable? Not ASI? Not other technologies, e.g. related to medicine and neuroscience? Seems extremely unlikely to me. Think of how much has changed in the last 100 years, and the rate of change has only accelerated since then.
I agree that intellectuals were in favor of communism when communism was a new thing. (These days, in the post-communist countries, it is the other way round.) But I still think that on average, smarter people generate more positive externalities. Basically, most useful things we see around us were invented by someone smart.
Caplan’s argument about outsourcing less challenging tasks to others has a few problem. First, smart people doing simple things is a waste of talent only because the smart people are rare (and if you let them do simple things, it means that the complicated things will not get done). In a society of Einsteins it wouldn’t matter that some of them do the dishes, because there would still be enough of them left to invent the cool stuff. Second, anecdotal evidence suggests that the division of labor works worse than advertised; a few of my friends have complained to me about horrible job that was done by various manual workers e.g. when they hired someone to build or reconstruct their houses, so they ultimately had to find some tutorials on YouTube and fix the things themselves.
I agree about the prediction markets. (However, the main argument against them seems to be that the dumb people would immediately waste lost of money there, and then go and cause social unrest.)
And here’s an excerpt from her book:
I get what the author wants to say, but...
Facts are value-neutral. If you say e.g. “IQ exists”, will other people classify you as a good guy, or as a bad guy? If it’s predictably the latter, we won’t have enough “anti-eugenists”, because anyone non-autistic who cares about other people will be discouraged from studying IQ seriously.
What if the “least advantaged” e.g. dumb people actively want things that will hurt everyone (including the least advantaged people themselves, in long term)? Maybe the dumber they are, the more kids they want to have. Or maybe the dumber they are, the more they want to make decisions about scientific research. Should the biologically privileged respect them as equals (and e.g. let themselves get outvoted democratically), or should they say no?
Shortly, you can make it sound easy by ignoring how this stuff works in real world.
That’s not a criticism of Harden’s book though, right? I think she’s trying (among other things) to make it more socially acceptable to say that IQ exists.
Ah, good for them! Kids are wonderful! Let us celebrate life. Here’s a Bryan Caplan post for you.
I think that people of all IQs vote against their interests. I’m not even sure that the sign of the correlation is what you think it is; for example, intellectuals were disproportionately supportive of communism back in the day, even while Stalin and Mao were killing tens of millions. I’m sure you can think of many more such examples, which I won’t list right here in order to avoid getting into politics fights.
The answer to questions like “what if [group] wants [stupid thing]” is that various groups have always been wanting stupid things. We should just keep fighting the good fight to try to push things in a good direction on the margin. For example, I think prediction market legalization and normalization would be excellent, as would widespread truth-seeking AI tools, and of course plain old-fashioned “advocating for causes you believe in”, etc. If some people in society are unusually wise, then let them apply their wisdom towards crafting very effective advocacy for good causes, or towards making money and funding good things, etc.
And this whole thing is moot anyway, because I would be very surprised if the genetic makeup of any country changes more than infinitesimally (via differential fertility) before we get superintelligent AGIs making all the important decisions in the world. The idea of humans making important government and business decisions in a post-ASI world is every bit as absurd as the idea of moody 7-year-olds making important government and business decisions in today’s world. Like, you’re talking about small putative population correlations between fertility and other things. If those correlations are real at all, and if they’re robust across time and future cultural and societal and technological shifts etc., (these are very big and dubious “ifs”!), then we’re still talking about dynamics that will play out over many generations. You really think nothing is going to happen in the next century or two that makes your extrapolations inapplicable? Not ASI? Not other technologies, e.g. related to medicine and neuroscience? Seems extremely unlikely to me. Think of how much has changed in the last 100 years, and the rate of change has only accelerated since then.
I agree that intellectuals were in favor of communism when communism was a new thing. (These days, in the post-communist countries, it is the other way round.) But I still think that on average, smarter people generate more positive externalities. Basically, most useful things we see around us were invented by someone smart.
Caplan’s argument about outsourcing less challenging tasks to others has a few problem. First, smart people doing simple things is a waste of talent only because the smart people are rare (and if you let them do simple things, it means that the complicated things will not get done). In a society of Einsteins it wouldn’t matter that some of them do the dishes, because there would still be enough of them left to invent the cool stuff. Second, anecdotal evidence suggests that the division of labor works worse than advertised; a few of my friends have complained to me about horrible job that was done by various manual workers e.g. when they hired someone to build or reconstruct their houses, so they ultimately had to find some tutorials on YouTube and fix the things themselves.
I agree about the prediction markets. (However, the main argument against them seems to be that the dumb people would immediately waste lost of money there, and then go and cause social unrest.)