Skip to main content

The Real Problem with Charles Murray and "The Bell Curve"

The 1994 book, now seeing an unfortunate resurgence, investigates racial differences in IQ—without being honest about the authors' motives

This article was published in Scientific American’s former blog network and reflects the views of the author, not necessarily those of Scientific American


He's back. Recent college protests have propelled Charles Murray into the news cycle again, and his resurging book sales show the publicity's not all bad. Attempts to fully discredit his most famous book, 1994's "The Bell Curve," have failed for more than two decades now. This is because they repeatedly miss the strongest point of attack: an indisputable—albeit encoded—endorsement of prejudice.

"The Bell Curve" (co-authored with Richard Herrnstein) prevails as the flagship modern work reporting on racial differences in IQ score. Black people in the U.S. score lower on average than white people (this isn't the book's primary focus, but it's the centerpiece and main draw of attention). As much as progressives don't want to hear such a thing, this book puts it plainly: It's in the data. With the book’s standing intact, armchair sociologists at large may defend certain stereotypes by simply pointing its way. As for attempts to take the book down, most critics go after its reasoning or its sources (or the authors' associations with the more notorious sources). But those points should actually take a secondary position within a thorough rebuke. Let me clear my throat.

“The Bell Curve” endorses prejudice by virtue of what it does not say. Nowhere does the book address why it investigates racial differences in IQ. By never spelling out a reason for reporting on these differences in the first place, the authors transmit an unspoken yet unequivocal conclusion: Race is a helpful indicator as to whether a person is likely to hold certain capabilities. Even if we assume the presented data trends are sound, the book leaves the reader on his or her own to deduce how to best put these insights to use. The net effect is to tacitly condone the prejudgment of individuals based on race.


On supporting science journalism

If you're enjoying this article, consider supporting our award-winning journalism by subscribing. By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today.


And “Bell Curve” readers will apply this racial data indeed. After all, data is white hot these days—for the very reason that it drives better per-person decisions. I myself work in the big data area; I founded Predictive Analytics World, an international conference series that propels the deployment of data science across sectors. Organizations are leveraging data to better decide whom to mail, approve for a loan, investigate, incarcerate, set up on a date, or medicate. Faith in empirical, fact-based methods is growing. As 20th century techie William Deming put it, "In God we trust; all others must bring data."

Insights from data might serve you personally as well, deciding whom to trust, befriend, hire, rent to, or even marry. But there's a name for it if you were to base such decisions on a person's race or other protected class. And this label applies even if you interpret racial trends to stem entirely from environmental factors (rather than buying into the problematic claim that there's a genetic component). The practice is called prejudice.

This isn't the "PC police" talking. Although prejudice breaks taboos, stomps on eggshells, and hurts people's feelings with unfairness, that's just the beginning. Its full damage reaches much more dire extremes. Personhood and individuality are sacred. Judging by way of category is the epitome of dehumanizing. It curtails the individual's opportunities and livelihood, and contributes to what is often a self-fulfilling, systematic cycle of disadvantage for an entire group. It also curtails the prejudger's potential to wholly evaluate a person as an individual by his or her prior behavior, choices, and character. This is why the term "civil rights" has a nice ring to it and "bigotry" does not.

Strangely, "The Bell Curve" falsely promises that it will recommend specific uses for these racial trends in the form of public policies. If you weather the storm and make it through this lengthy book, you'll find that, by the end, it has never done so. In the final chapter (Chapter 22), when it finally delivers a few much-anticipated policy prescriptions, they don't relate to race in any explicit way (and how could they?). The suggested policies include simpler tax codes, decreasing government benefits that could incentivize childbearing among the low-income, and increasing competency-based immigration screening. Did the authors mean to imply that immigration screening could be based in part on race? Much to the book's disgrace, that's at least a reasonable interpretation. More so since, earlier in the book, they say, "Latino and black immigrants are, at least in the short run, putting some downward pressure on the distribution of intelligence."

It’s worth pointing out an astonishing slip-up where the authors appear to have inadvertently admitted that treating black people differently is copacetic (I felt I'd caught them red-handed). Ironically, it's within a section warning the reader that a genetic interpretation of the racial trends should not mean [more] prejudgment of individuals. When suggesting a thought experiment in which the reader imagines IQ differences were known to originate entirely genetically, they suggest you ask yourself, "If it were known that the black/white difference is genetic, would I treat individual blacks differently from the way I would treat them if the differences were environmental?" This plainly implies that one may already be treating individual black people differently in the first place.

With a certain eerie silence on the matter, "The Bell Curve" spurs readers to prejudge by race. Astonishingly, this tome's hundreds of pages never actually specify what one is meant to do with the information about racial differences, and never attempt to steer readers clear of racial prejudgment. That's an egregious, reckless oversight, considering this is a pop science bestseller that comprehensively covers great numbers of subtopics and caveats, maintaining a genuinely proficient and clear writing style throughout. So we must call this book what it is: racist.

Eric Siegel, PhD, is the author of Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die, Revised and Updated Edition (Wiley, January 2016), founder of the Predictive Analytics World conference series, executive editor of The Predictive Analytics Times, and a former computer science professor at Columbia University.

More by Eric Siegel