“Celebrating” does not mean passing laws. It means that the people who sit at the apex of the nation’s politics, economics, and culture need to be advocates for marriage, community, productive work, and, at the least, to treat religion with respect. Large numbers of them fail that test and have failed it for decades. The members of the new upper class avail themselves of the wellsprings. They marry, raise children, live in communities they find satisfying, work hard, and some of them are religious. But they don’t even acknowledge that they are tapping into the traditional sources of human flourishing, let alone celebrate ordinary Americans who do. Instead, their attitude toward ordinary Americans is too often covertly condescending if they are people of color and openly disparaging if they are white. What are the policy implications of Human Diversity? They don’t constitute a policy agenda. They involve the human heart, not legislation or regulations. The first step is to reconstruct a moral vocabulary for discussing human differences.
Reconstructing a Moral Vocabulary for Discussing Human Differences
A century ago, Walter Lippmann, then one of the nation’s most influential public intellectuals, wrote of IQ tests, “I hate the impudence of a claim that in fifty minutes you can judge and classify a human being’s predestined fitness in life. I hate the pretentiousness of that claim. I hate the abuse of scientific method which it involves. I hate the sense of superiority which it creates, and the sense of inferiority that it imposes.”37 Among many people, polygenic scores prompt the same anger and revulsion. They foresee dystopian futures in which polygenic scores are used to judge and classify a human being’s predestined fitness in life according not just to IQ but other cognitive traits as well. Personality traits. Potential for mental illness. Potential for criminality.
The dystopian dangers are real, but so are wonderful opportunities to use our new knowledge to do good. We won’t avoid the dangers and take advantage of the opportunities until we are able to talk easily and realistically about human differences. And yet so few try to do it. The conversation today within the new upper class seems always to be about the ways in which individual differences are created by environmental conditions that we must fix. It is seldom about how to deal with differences that can’t be fixed.
Why? I think at the root is the new upper class’s conflation of intellectual ability and the professions it enables with human worth. Few admit it, of course. But the evolving zeitgeist of the new upper class has led to a misbegotten hierarchy whereby being a surgeon is better in some sense of human worth than being an insurance salesman, being an executive in a high-tech firm is better than being a housewife, and a neighborhood of people with advanced degrees is better than a neighborhood of high school graduates. To put it so baldly makes it obvious how senseless it is. There shouldn’t be any relationship between these things and human worth. And yet, among too many in the new upper class, there is.
The conflation of intellectual ability with human worth helps to explain the new upper class’s insistence that inequalities of intellectual ability must be the product of environmental disadvantage. Many people with high IQs really do feel sorry for people with low IQs. If the environment is to blame, then those unfortunates can be helped, and that makes people who want to help them feel good. If genes are to blame, it makes people who want to help them feel bad. People prefer feeling good to feeling bad, so they engage in confirmation bias when it comes to the evidence about the causes of human differences.
I expect the genomics and neuroscientific revolutions to give us undeniable evidence that differences in personality, abilities, and social behavior exist across individuals and groups alike and that those differences cannot be much reduced by the kinds of public policy changes that are available to us. For America, the old way of dealing with that reality was the moral vocabulary of Christianity. We are all deeply flawed—sinners—and we are all the beneficiaries of God’s unearned love and grace. We are all equal in God’s eyes. That theological foundation, combined with America’s devotion to individual freedom, underwrote a signature feature of American exceptionalism: our egalitarianism. One of our proudest boasts was that in the United States, people aren’t better than anyone else just because they have more money or a higher position. We didn’t live by that ideal perfectly, but we did much better than many people realize. In living memory, it was considered un-American to be a snob, to look down on other Americans, and to think you were better than anyone else.
The moral vocabulary we must reconstruct for twenty-first century America cannot be Christian nor even ecumenically religious. Society in general and the new upper class in particular are too secular for that. The only choice left to us is a secular understanding of the truth behind the old formulation, “We are all equal in God’s eyes.” That secular understanding begins with the recognition that personality humility is not optional but compulsory. If you possess unusual beauty, charm, intellect, or talent of any sort, pride is inappropriate. Go ahead and take satisfaction in the use you have made of your gifts (with a mental caveat that some of the resources you called on are partly heritable too), but live with the consciousness of how incredibly lucky you were to have been born that way and try to be worthy of it.
Humility is the first step in coming to grips with a secular version of “we are all equal in God’s eyes,” but the fullness and depth of that truth cannot be apprehended abstractly. It needs to be understood through experience. That starts with realizing that most people are good, competent, and likeable, including those who don’t have much in common with you—even, amazingly, people who don’t share your politics. The more kinds of people you know and the better you know them, the easier it is to recognize that “equality of human worth” isn’t just rhetoric. You will also find it is easy to talk about the reality of human differences if you know in your gut how unimportant those differences are in deciding whether the person next to you is someone you respect. My prescription for the new upper class: Get out more.
When we are able once again to talk easily about human differences, a difficult and elusive next step remains. The wellsprings of human flourishing have been going dry for many Americans, and the damage done by the new upper class—however inadvertently—has been importantly to blame. Replenishing and revitalizing those wellsprings should be our first priority. But developing policies that replenish and revitalize them must begin with a drastic shift in the thinking of most of the people who run the nation’s economy, culture, and politics. It is time for America’s elites to try living with inequality of talents, understanding that each human being has strengths and weaknesses, qualities we admire and qualities we do not admire, and that our good opinion seldom turns on a person’s talents, but rather on a person’s character. We need a new species of public policy that accepts differences and works with people as they are, not as we want to shape them. I hope this book contributes to that process.
Acknowledgments
I began work on Human Diversity with curiosity but only an informed amateur’s knowledge about either genetics or neuroscience. As I always have done when taking on an unfamiliar discipline, my first step was to find recent technical articles on topics of interest and use the literature reviews to start tunneling into the subject matter.
The difference between this time and all the previous times was the breathtaking complexity of the articles I was reading. The nomenclature alone was daunting, but that was nothing compared to the substance. The processes required to go from a SNP to a synthesized protein and then from proteins to effects on the phenotype were not only stranger than I knew, but stranger than I could have imagined. Neuroscience was no easier, with nomenclature as unfamiliar and brain structure and function as complicated.
As I promised in the introduction, I stuck to the low-hanging fruit, but it was obvious that I would need experts to save me from blunders. I adopted two strategies. First, I emailed drafts of my work to the lead authors of the technical articles that I discussed at length, asking them to tell me
what I’d gotten wrong. Second, I asked geneticists, neuroscientists, and behavior geneticists who were most well versed in these topics to read long sections of text and vet them for errors of fact or interpretation.
I am a controversial figure. The last thing a geneticist or neuroscientist working on a college campus needs is to be thanked publicly by me. I therefore added a promise to all my requests for review: “Your response will not be used in any way except to improve the accuracy of the text. You will not be listed in the acknowledgments nor will I disclose in any forum that you saw the draft.” That’s why I’m not going to give you a single name of the many who responded to my requests (many did not) and to whom I am so indebted. I hope they understand how grateful I am. I have a special soft spot for those who responded to drafts that contained criticism of their work. In return, I did my best to revise the text until they saw the presentation as fair, even though residual disagreements remained.
I can safely thank a few people by name. E. O. Wilson, the pioneer of sociobiology, planted the seeds of Human Diversity by writing Consilience: The Unity of Knowledge, which I read when it first appeared in 1998. I was immediately convinced that Wilson was right, and my excitement about the integration of the social sciences with biology has stuck with me ever since. Arthur Brooks, AEI’s president, and Karlyn Bowman and Ryan Streeter, successively the directors of social and political studies at AEI as I worked on Human Diversity, were wholly supportive. Sean Desmond, editor of two of my earlier books, returned to lend his wise editorial counsel and to make the text much more readable. Roland Ottewell, my official copy editor, and Miles Hoffman, my unofficial one and friend of 35 years, meticulously scrutinized a late draft of the complete text. My agent, Amanda Urban, operated as she has since she took me on in 1984: the good shepherd making sure her author is treated right, morphing into a lioness as needed. None of this help means that no errors remain. An anxious aspect of publishing a complicated book is knowing that mistakes must still be hiding in there.
My wife and editor, Catherine, who has featured in so many acknowledgments, initially tried to talk me out of writing Human Diversity. When I began work in the fall of 2016, the nastiness associated with the reaction to The Bell Curve was a distant memory. Did I really want to go through that again? I didn’t think it would be a big deal one way or the other, but I was concerned that she was concerned. Then came the radicalization of the campuses, when we learned that the bad old days were back no matter what. “Confound it!” said Catherine, or two syllables to that effect, on the day I returned from the riot at Middlebury. “If they’re going to do this kind of thing anyway, go ahead and write it.” Human Diversity appears with her blessing, which was absolutely essential. She is the coauthor of my life.
Charles Murray
Burkittsville, Maryland
July 29, 2019
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About the Author
Charles Murray is the F. A. Hayek Emeritus Scholar in Cultural Studies at the American Enterprise Institute, where he has worked for thirty years. He was raised in Iowa, educated at Harvard and MIT, and came of age in Thailand. The father of four children, he is married to Catherine Cox and lives in Burkittsville, Maryland.
Appendix 1
Statistics for People Who Are Sure They Can’t Learn Statistics
The following is aimed at the liberal arts graduate who has not taken a math course since high school and knows nothing whatsoever about statistics but wants to understand the statistical concepts used in the text.
Distributions and Standard Deviations
Why Do We Need “Standard Deviation”?
Every day, formally or informally, people make comparisons—among people, among apples and oranges, among dairy cows or egg-laying hens, among the screws being coughed out by a screw machine. The standard deviation is a measure of how spread out the things being compared are. “This egg is a lot bigger than average,” a chicken farmer might say. The standard deviation gives him a way of saying precisely what he means by “a lot.”
What Is a Frequency Distribution?
To get a clear idea of what a frequency distribution is, imagine yourself back in your high school gym, with all the boys in the senior class assembled before you (including both sexes would complicate matters, and the point of this discussion is to keep things simple). Line up these boys from left to right in order of height.
Now you have a long line going from shortest to tallest. As you look along the line you will see that only a few boys are conspicuously short and tall. Most are in the middle, and a lot of them seem identical in height. Is there any way to get a better idea of how this pattern looks?
Tape a series of cards to the floor in a straight line from left to right, with “60 inches and shorter” written on the one at the far left, “80 inches and taller” on the card at the far right, and cards in one-inch increments in between. Tell everyone to stand behind the card that corresponds to his height.
Someone loops a rope over the rafters and pulls you up in the air so you can look straight down on the tops of the heads of your classmates standing in their single files behind the height labels. The figure below shows what you see.
This is a frequency distribution. What good is it? Looking at your high school classmates standing around in a mob, you can tell little about their height. Looking at those same classmates arranged into a frequency distribution, you can tell a lot, quickly and memorably.
How Is the Distribution Related to the Standard Deviation?
We still lack a convenient way of expressing where people are in that distribution. What does it mean to say that two different students are, say, six inches different in height? How “big” is a six-inch difference? That brings us back to the standard deviation.
When it comes to high school students, you have a good idea of how big a six-inch difference is. But what does a six-inch difference mean if you are talking about the height of elephants? About the height of cats? It depends. And the things it depends on are the average height and how much height varies among the things you are measuring. A standard deviation gives you a way of taking both the average and that variability into account, so that “six inches” can be expressed in a way that means the same thing for high school students relative to other high school students, elephants relative to other elephants, and cats relative to other cats.
How Do You Compute a Standard Deviation?
Suppose that your high school class consisted of just two people, who were 66 inches and 70 inches tall. Obviously, the average is 68 inches. Just as obviously, one person is 2 inches shorter than average, one person is 2 inches taller than average. The standard deviation is a kind of average of the differences from the mean—2 inches, in this example. Suppose you add two more people to the class, one who is 64 inches and the other who is 72 inches. The mean hasn’t changed (the two new people balance each other off exactly). But the newcomers are each 4 inches different from the average height of 68 inches. So the standard deviation, which measures the spread, has gotten bigger as well. Now two people are 4 inches different from the average and two people are 2 inches different from the average. That adds up to a total of 12 inches, divided among four persons. The simple average of these differences from the mean is 3 inches, which is almost (but not quite) what the standard deviation is. To be precise, the standard deviation is calculated by squaring the deviations from the mean, then summing them, then finding their average, then taking the square root of the result. In this example, two people are 4 inches from the mean and two are 2 inches from the mean. The sum of the squared deviations is 40 (i.e., 16 + 16 + 4 + 4). Their average is 10 (40 ÷ 4). The square root of 10 is 3.16, which is the standard deviation for this example. The technical reasons for using the standard deviation instead of the simple average of the deviations from the mean are not necessary to go into
, except that in normal distributions, the standard deviation has wonderfully convenient properties. If you are looking for a short, easy way to think of a standard deviation, “the average difference from the mean” is close enough.
As an example of how a standard deviation can be used to compare apples and oranges, suppose we are looking at members of the Olympic women’s gymnastics team and professional basketball players. You notice a woman who is 5 feet 6 inches and a man who is 7 feet. You know from watching gymnastics on television that 5 feet 6 inches is tall for a woman gymnast and 7 feet is tall even for a basketball player. But you want to do better than a general impression. Just how unusual is the woman, compared to the average gymnast on the U.S. women’s team, and how unusual is the man, compared to the average professional basketball player?
We gather data on height among the women gymnasts and determine that the mean is 5 feet 1 inch with a standard deviation (SD) of 2 inches (made-up numbers for this example). For professional basketball players, we find that the mean is 6 feet 6 inches and the SD is 4 inches. Thus the woman who is 5 feet 6 inches is 2.5 standard deviations taller than the average; the seven-foot man is only 1.5 standard deviations taller than the average. These numbers—2.5 for the woman and 1.5 for the man—are also the basis for effect sizes introduced in chapter 1. Now we have an explicit numerical way to compare how different the two people are from their respective averages, and we have a basis for concluding that the woman who is 5 feet 6 inches is a lot taller relative to other female Olympic gymnasts than a 7-foot man is relative to other professional basketball players.
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