Initially, most of the psychology profession accepted the startling claim that one’s predilection to discriminate in real life is revealed by the microsecond speed with which one sorts images. But possible alternative meanings of a “pro-white” IAT score are now beginning to emerge. Older test-takers may have cognitive difficulty with the shifting instructions of the IAT. Objective correlations between group membership and socioeconomic outcomes may lead to differences in sorting times, as could greater familiarity with one ethnic-racial group compared with another. These alternative meanings should have been ruled out before the world learned that a new “scientific” test had revealed the ubiquity of prejudice.
The most recent meta-analysis deals another blow to the conventional IAT narrative. This study, not yet formally published, looked at whether changes in implicit bias allegedly measured by the IAT led to changes in “discriminatory behavior”—defined as the usual artificial lab conduct. While small changes in IAT scores can be induced in a lab setting through various psychological priming techniques, they do not produce changes in behavior, the study found.
The analyses’ seven authors propose a radical possibility that would halt the implicit-bias crusade in its tracks: “perhaps automatically retrieved associations really are causally inert”—that is, they have no relationship to how we act in the real world. Instead of “acting as a ‘cognitive monster’ that inevitably leads to bias-consistent thought and behavior,” the researchers propose, “automatically retrieved associations could reflect the residual ‘scar’ of concepts that are frequently paired together within the social environment.” If this is true, they write, there would need to be a “reevaluation of some of the central assumptions that drive implicit bias research.” That is an understatement.
Among the study’s authors are Brian Nosek of the University of Virginia and Calvin Lai of Washington University in St. Louis. Both have collaborated with Greenwald and Banaji in furthering the dominant IAT narrative; Nosek was Banaji’s student and helped put the IAT on the web. It is a testament to their scientific integrity that they have gone where the data have led them. (Greenwald warned me in advance about their meta-analysis: “There has been a recent rash of popular press critique based on a privately circulated ‘research report’ that has not been accepted by any journal, and has been heavily criticized by editor and reviewers of the one journal to which I know it was submitted,” he wrote in an email. But the Nosek, Lai, et al., study was not “privately circulated”; it is available on the web, as part of the open-science initiative that Nosek helped found.)
The fractious debate around the IAT has been carried out exclusively at the micro-level, with hundreds of articles burrowing deep into complicated statistical models to assess minute differences in experimental reaction times. Meanwhile, outside the purview of these debates, two salient features of the world go unnoticed by the participants: the pervasiveness of racial preferences and the behavior that lies behind socioeconomic disparities.
One would have difficulty finding an elite institution today that does not pressure its managers to hire and promote as many blacks and Hispanics as possible. Nearly 90 percent of Fortune 500 companies have some sort of diversity infrastructure, according to corporate diversity trainer Howard Ross. The federal Equal Employment Opportunity Commission requires every business with a hundred or more employees to report the racial composition of its workforce. Employers know that empty boxes for blacks and other “underrepresented minorities” can trigger governmental review.
Some companies tie manager compensation to the achievement of “diversity,” as Roger Clegg documented before the US Civil Rights Commission in 2006. “If people miss their diversity and inclusion goals, it hurts their bonuses,” Miles White, the CEO of Abbott Laboratories, said in a 2002 interview. Since then, the diversity pressure has only intensified. Google’s “objectives and key results” for managers include increased diversity. Walmart and other big corporations require law firms to put minority attorneys on the legal teams that represent them. “We are terminating a firm right now strictly because of their inability to grasp our diversity expectations,” Walmart’s general counsel announced in 2005. Any reporter seeking a surefire story idea can propose tallying up the minorities in a particular firm or profession; Silicon Valley has become the favorite subject of bean-counting “exposés,” though Hollywood and the entertainment industry are also targets of choice, especially in the #MeToo era (see chapter 9). Organizations will do everything possible to avoid such negative publicity.
In colleges, the mandate to hire more minority (and female) candidates hangs over almost all faculty recruiting. Deans have canceled faculty-search results and ordered the hiring committee to go back to the drawing board if the finalists are not sufficiently “diverse.” As previously discussed, every selective college today admits black and Hispanic students with much weaker academic qualifications than those of white and Asian students, as any high school senior knows. At the University of Michigan, an Asian with the same GPA and SAT scores as the median black admit had zero chance in 2005 of admission; a white with those same scores had a 1-percent chance of admission. At Arizona State University, a white with the same academic credentials as the average black admit had a 2-percent chance of admission in 2006; that average black had a 96-percent chance of admission. The preferences continue into graduate and professional schools. From 2013 to 2016, medical schools nationally admitted 57 percent of black applicants with low MCATs of 24 to 26 but only 8 percent of whites and 6 percent of Asians with those same low scores, as Claremont McKenna College’s Frederick Lynch reported in The New York Times.2 The reason for these racial preferences is administrators’ burning desire to engineer a campus with a “critical mass” of black and Hispanic faces.
Similar pressures exist in the government and nonprofit sectors. In the New York Police Department, blacks and Hispanics are promoted ahead of whites for positions to which promotion is discretionary, as opposed to being determined by an objective exam. In the 1990s, blacks and Hispanics became detectives almost five years earlier than whites and took half the time as whites did to be appointed to deputy inspector or deputy chief.
And yet, we are to believe that alleged millisecond associations between blacks and negative terms are a more powerful determinant of who gets admitted, hired, and promoted than these often-explicit and heavy-handed preferences. If a competitively qualified black female PhD in computer engineering walks into Google, say, we are to believe that a recruiter will unconsciously find reasons not to hire her, so as to bring on an inferior white male. The scenario is preposterous on its face—in fact, such a candidate would be snapped up in an instant by every tech firm and academic department across the country. The same is true for competitively qualified black lawyers, accountants, and portfolio managers.
If such discrimination is so ubiquitous, there should be victims aplenty that the proponents of implicit bias can point to. They cannot.
I twice asked Anthony Greenwald via email if he was aware of qualified candidates in faculty searches anywhere who were overlooked or rejected because of skin color. He ignored the question. I twice asked Jerry Kang’s special assistant for equity, diversity, and inclusion via email if Vice Chancellor Kang was aware of faculty candidates for hire or promotion at UCLA or elsewhere who were overlooked because of implicit bias. Kang’s assistant ignored the question. Howard Ross has been a prominent corporate diversity trainer for thirty years, with clients that include hundreds of Fortune 500 companies, Harvard and Stanford medical schools, and two dozen other colleges and universities. I asked him in a phone interview if he was aware of the most qualified candidate for a business or academic position not getting hired or promoted because of bias. Ross merely said that there was a “ton of research that demonstrates that it happens all the time,” without providing examples.
PricewaterhouseCoopers has spearheaded an economy-wide diversity initiative, dubbed the CEO Action for Diversity & Inclusion�
��. Nearly two hundred CEOs have signed a pledge to send their employees to implicit-bias training; in the case of PricewaterhouseCoopers, that means packing off fifty thousand employees to the trainers. Any organization spending a large sum of money on a problem would presumably have a firm evidentiary basis that the problem exists. Megan DiSciullo is a spokesman for the CEO Action for Diversity & Inclusion and a member of PricewaterhouseCoopers’s human resources department. I asked her if she was aware of candidates who should have been hired at PwC but weren’t because of implicit bias. Our telephone exchange went as follows:
DiSciullo: I’m not aware of someone not getting a job because of bias.
Me: But are your managers making suboptimal decisions because of bias?
DiSciullo: The coalition as a group recognizes that everyone has unconscious bias; we are committed to training our managers to be better.
Me: Your managers are not making optimal decisions because of bias?
DiSciullo: Everyone has unconscious bias. I’m not saying that anyone is not being hired or promoted, but it’s part of the workplace.
Me: In what way? People are being treated differently?
DiSciullo: People have bias, but it manifests itself differently. I think you have an agenda, which I am trying to unpack. The facts are clear that people have biases and that they could bring them to the workplace. Corporations recognize that fact and want to build the most inclusive workplace.
Me: You base the statement that everyone has biases on what?
DiSciullo: On science and on the Harvard Business Review.
Other signatories to the CEO Action for Diversity & Inclusion include Cisco, Qualcomm, KPMG, Accenture, HP, Procter & Gamble, and New York Life, several of which are on the steering committee. These companies either failed to respond to preliminary requests for an interview about the CEO Action for Diversity & Inclusion or went silent when asked if they knew of implicit bias infecting hiring and promotion decisions. Obviously, such reticence may be motivated by a fear of litigation. But it is also likely that there are no known victims of implicit bias.
The insistence that implicit bias routinely denies competitively qualified minority candidates jobs and promotions also requires overlooking the relentless pressure to take race into account in employment and admissions decisions. I asked Greenwald if implicit bias overrides these institutional pressures to hire and promote by race. He evaded the question. “‘Override’ is the wrong word,” he wrote back. “Implicit biases function as filters on perception and judgment, operating outside of awareness and often rendering perception and judgment invalid.” In response to a follow-up question, he denied that those institutional pressures were all that strong, as evidenced by the fact that many diversity programs produced no “beneficial effect.” Another explanation for the persistent lack of proportional representation in the workplace, however, is that there are not proportional numbers of qualified minorities in the hiring pipeline.
Diversity trainers invoke behavioral economics to explain why explicit diversity mandates don’t override implicit bias. This field, popularized by the work of cognitive psychologist Daniel Kahneman, has shown that people often fail to use information in rational ways. “We now know that most decisions are visceral and emotional,” said Ross, in response to my incredulity that a university physics department would not leap at a competitively qualified black PhD candidate. Joelle Emerson, a high-profile diversity trainer in Silicon Valley, claims that because companies are “not purely rational actors,” they will as a group discriminate against the most qualified candidate. “People will be left out of entire industries,” she said. “People from stereotyped groups have a harder time getting hired and promoted.”3
But incentives can overcome the flaws in rational analysis identified by behavioral economics. The incentive for race-conscious employment decisions is so strong that the burden of proof is on those who maintain that implicit bias will override it. The fact is that blacks on the academic market and in many other fields enjoy a huge hiring advantage.
Yet they are still not proportionally represented in the workplace, despite decades of trying to engineer “diversity.” You can read through hundreds of implicit-bias studies and never come across the primary reason: the academic skills gap. Given the gap’s size, anything resembling proportional representation can be achieved only through massive hiring preferences.
From 1996 to 2015, the average difference between the mean black score on the math SAT and the mean white score was 0.92 standard deviation, reports a February 2017 Brookings Institution study. The average black score on the math SAT was 428 in 2015; the average white score was 534, and the average Asian score was 598. The racial gaps were particularly great at the tails of the distribution. Among top scorers—those scoring between 750 and 800—60 percent were Asian, 33 percent were white, and 2 percent were black. At the lowest end—scores between 300 and 350—6 percent were Asian, 21 percent were white, and 35 percent were black. If the SATs were redesigned to increase score variance—that is, to spread out the scores across a greater range by adding more hard questions and more easy questions—the racial gaps would widen.
The usual poverty explanations for the SAT gap don’t hold up. In 1997, white students from households with incomes of $10,000 or less scored better than black students from households with incomes of $80,000 to $100,0004. In 2015, students with family incomes of $0 to $20,000 (a category that includes all racial groups) had a higher average math SAT score (455) than the average math SAT score of black students from all income levels (435). At the University of California, race predicts SAT scores better than class. Proponents of racial preferences routinely claim that the SATs are culturally biased and do not measure actual cognitive skills. If that were the case, blacks would do better in college than their SAT scores would predict. As discussed in chapter 2, blacks do worse. Further, the math test is not amenable to the “cultural-bias” criticism (unless one believes that math is itself biased). Low scores reflect an actual difficulty with math. In 2016, 54 percent of black elementary and high school students in California, for example, did not meet the state’s math standards, compared with 21 percent of white students and 11 percent of Asian students. The chancellor of the California Community Colleges system proposed in July 2017 that intermediate algebra be removed from graduation requirements for associate’s degrees because blacks and Hispanics have such a hard time passing the course. Math difficulties are the greatest reason that, in California, only 35 percent of black students earn their associate’s degrees, compared with 54 percent of whites and 65 percent of Asians.
The math SAT and algebra require abstract quantitative reasoning. The math achievement gap will most affect hiring in fields with advanced quantitative requirements. In 2016, 1 percent of all PhDs in computer science went to blacks, or 17 out of 1,659 PhDs, according to the Computing Research Association’s annual Taulbee Survey. Three blacks received a PhD in computer engineering, or 3.4 percent of the total. Blacks earned 0.7 percent of master’s degrees in computer science and 3 percent of undergraduate degrees in computer science. Yet the biggest Silicon Valley firms are wedded to the idea that their own implicit bias is responsible for the racial (and gender) composition of their workforce. A member of Google’s “People Analytics” (i.e., HR) department, Brian Welle, lectures widely about implicit bias and the IAT; Google declined to let me interview him or a People Analytics colleague.
A host of other professions beyond the sciences draw on the analytic skills required by algebra and the math SAT. Business management and consulting, for example, call for logic and conceptual flexibility. Anyone in medicine, including nursing, should be able to master basic algebra. These professions should not be tainted with the implicit-bias charge when they are hiring from the same finite pool of competitively qualified blacks.
The SAT’s verbal sections show the same 100-point test-score gap between whites and blacks as the math section. Pace the critics, that is not an artifact
of cultural bias: The average black twelfth-grader reads at the level of the average white eighth-grader. In California in 2016, 44 percent of black students through the high school grades did not meet state standards in English language arts and literacy, compared with 16 percent of white students and 11 percent of Asian students.5
Like the SAT, the LSAT also measures reading comprehension and verbal reasoning. It has a greater test-score gap than the SAT: 1.06 standard deviations between average black and white scores in 2014. If the LSAT test-score gap were the result of cultural bias, the LSAT would underpredict black performance in law school. It does not. The majority of black law students cluster in the bottom tenth of their class, thanks to racial preferences in admissions, as mentioned in chapter 2. The median black law school GPA is at the sixth percentile of the median white GPA, meaning that 94 percent of whites do better than the median black. This achievement gap cannot be chalked up to implicit bias on the part of law school professors. The overwhelming majority of law school exams are still graded blind, meaning that the identity of the test-taker is concealed from the grader. The bar exam is also graded blind. If blacks were discriminated against in law school by professors, they should do better on the bar exam than their GPAs would predict. They do not. A 1998 study by the Law School Admissions Council found that 22 percent of black test-takers never pass the bar examination after five attempts, compared with 3 percent of white test-takers. Yet the relatively low number of blacks among law firm partners is routinely attributed—by the firms themselves—to hiring and promotion committee bias. In fact, corporate law firms hire blacks at rates that exceed their representation among law school graduates. But because the preferences in their favor are so large—the law school GPAs of black associates are at least a standard deviation below those of white associates—black attrition from corporate firms is high. By the time the partnership decision rolls around, few black associates remain at their firms to be promoted, as UCLA’s Richard Sander has shown.
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