Cavani did not realise that under this dispensation, mere absence of intent was not enough to prove innocence, and was not even a mitigating circumstance.
Black Americans broadly report they need to work harder and be better qualified than white Americans merely to receive equal consideration for jobs and other opportunities. Whites generally say they hold no racial animus toward blacks. These reports seem to contradict each other, but they aren’t. The fact that both can be true at the same time points both to barriers to, and possibilities for, racial progress in America.
The irony is that the racial inequalities in America today can sustain themselves without racial bias among whites. This is the implication of a large swath of the literature on “implicit bias.” The inapt phrase itself—implicit bias—masks the implication. The phrase misfocuses attention on what much of its own literature suggests is the wrong variable, and, hence, on the wrong remedy.
Lest I be misunderstood, let me state the obvious: racial economic inequality today certainly reflects the legacy of racism in America. The puzzle, however, is this: Why hasn’t racial inequality decreased along with the decrease in racial animus?
Many on both the left and the right deny there is a puzzle. On the left, white protestations that they do not harbor racial animus are discounted as reflections only of social desirability bias—that most whites will not admit what they in fact believe about blacks. On the right, legal prohibition of racial discrimination, and widespread affirmative action policies, result in discounting the continuing reports from black Americans of needing to work harder and be better qualified than whites to be considered for a given job or opportunity.
The seeming contradiction in beliefs stokes racial resentment in both groups: among whites because they’re accused of racism even when they harbor no racial animus, and among blacks because whites discount what they experience every day.
To be sure, while bias certainly is a sufficient condition for the patterns of racial inequality we see today, bias is not a necessary condition for the patterns of racial inequality we see today. Yet, ironically, continuing racial bias is not a necessary condition for blacks accurately to understand they generally need to better qualified than whites to compete successfully for a given job or opportunity.
How can that be?
Before turning to the explanation we might note the two important policy implications that follow from recognizing both experiences can be true at the same time. First, even if or when racial prejudice has truly disappeared, that fact alone would not necessarily eliminate racial economic disparities. That’s the challenge. The good news, however, is this: attention to individual merit would minimize the effects of “implicit bias” for individual job candidates. That’s the direct effect. But there would also be an indirect, more systemic effect by establishing for black Americans the same rewards for achievement that white Americans already enjoy.
Now let’s turn to the explanation.
There are a cluster of theoretical accounts that get grouped under the title of “implicit bias.” What I might call the “information-cost” theory of racial disparities, or perhaps the “search-cost” theory sits somewhat awkwardly under the title. Not least because it can account for the continuation of those disparities even without racial bias, whether implicit or not.
There are at least two components to this account. The first is that, in interacting with people, all individuals draw on what they know of the characteristics of groups to which those people belong. There is a time component to this, however. We draw on what we believe of group characteristics particularly when they do not know the other person very well or are just getting to know them.
And, of course, people have all sorts of identifiable features—not just race—that associate us with different with different groups. When others “see” us, particularly for the first time, they often will use what they know about common or “average” characteristics of these groups to form their initial, preliminary beliefs about us. In essence, when we first me other people, they are largely a blank canvas to us. So we use group averages to fill in the vast blank areas on the canvas as we (implicitly) consider how we will interact with them initially.
The critical two words here are “group averages.” A person looks at me, sees, say, my gray hair. From that, before they know me more particularly—before they have time to know me more particularly—they make certain initial assessments about what I am like based on what they know about the population of “gray-haired males.” These assessments are contingent, to be sure, but they are assessments nonetheless.
Mind you, all of these assessments are simply based on averages or perceived commonalities among gray-haired males.
To be sure, people see more than my gray hair—there are lots of “intersectionalities.” That I wear a wedding band. That I’m overweight. That I look haggard, or have laugh wrinkles around my eyes, and so forth. How I’m dressed. And, certainly also, that I’m white.
If the person gets to know me better, then many of the suppositions made based on population averages will get updated based on the information they learn about me as an individual. But, critically, most of the people whom I meet during the day will never know me better than from our brief interaction.
This process is almost always an “implicit” psychological process. But while it is typically an implicit process, it is not necessarily a “biased” process.
What the other people believe regarding the commonalities or averages of the different populations to which I belong can be entirely correct in their assessment of those averages. This provides a serviceable standard from which to define “bias”: A person is “biased” when that person’s belief about the average characteristic of a population diverges from the true average of that population.
But even when a person holds true beliefs about a population—when he or she holds “unbiased” beliefs about a population—individuals within those populations deviate from those averages all the time, sometimes significantly.
This deserves emphasis. People can have entirely accurate beliefs about averages or commonalities in populations to which others belong. But averages are just that, averages. It takes additional time and attention to update one’s assessment of a person’s individual characteristics and capabilities.
Let’s now bring the discussion home to race-based economic inequality.
Consider the large set of experimental results in which substantively identical résumés are submitted for consideration for a job. What differs is the use of “racially identifiable” names on the résumés. Some of the résumés have names commonly identified as “African American names,” others have names commonly identified as “white names.”
The consistent outcome is that callbacks for résumés with names identified with African Americans are significantly lower than callbacks for résumés with names identified with whites.
To be sure, this outcome is entirely consistent with the existence of racial bias. Yet the outcome is not necessarily the result of racial animus.
Consider a hiring manager who has 200 résumés to review before lunch. The amount of time the manager can spend on any one résumé at the preliminary review stage is maybe fifteen seconds. As a general matter, the manager is looking for candidates with good reading, writing, and arithmetic skills. The hiring manager also knows because of access to worse educational opportunities on average, African Americans on average have lower reading, writing, and arithmetic skills than white Americans. In the press to sort the résumés within the limited time allotted the manager makes quick judgments on the set of finalists.
Because of time-pressured reliance on population averages, the manager selects a disproportionately high number of whites for the callback file and a disproportionately low number of African Americans. Not because of prejudice or bias, but as a result of population averages and time constraints.
Several notable implications follow from this. First, note there is a misalignment between the individual incentives the manager faces and the company’s goals. The company wants the hiring manager to hire the most qualified applicants for the jobs it has. But because of the time pressure the hiring manager faces to review the initial round of applications quickly, he or she often draws on population averages to fill in the blanks on applicants. These “blanks” may not in fact literally be blanks on the résumés. But the hiring manager doesn’t see the information in skimming over the résumés.
As a result of this context, however, the hiring manager actually excludes qualified African Americans from the callback list because of the informational shortcuts the hiring manager has to use to get the job done.
Mitigating the misaligned incentives facing the hiring manager—often simply a matter of allocating a little more time for a more in-depth review of the initial set of applications—means the company would now interview and hire more African American applicants because the review process now better identifies the most qualified applicants. Note that this problem of racial inequality is in fact mitigated by sharper focus on the individual merits of the applicants.
Now flip the focus to the black experience. The theory states that to get the attention of hiring managers African American applicants on average need to be better qualified than the corresponding white applicant. This is what African Americans report as their experience. To get the same attention, African Americans need to have better qualifications.
This, however, is only the direct effect. Consider the feedback loop created by the current experience. As a systematic matter, black Americans on average receive lower payoffs for the same level of education and experience as white Americans. Well, just do the math: Less profit, less investment. The feedback loop sustains race-based economic inequality. Simply hiring qualified African American applicants at the same rate as similarly-qualified whites are hired would be a big step to equalizing incentives for achievement across the races in America, and thereby equalizing achievement.
“Implicit bias” is an unfortunate title for this line of research. It focuses attention on something—the existence of “bias”—that is not necessary to account for the existence of racial economic disparities. As a result, it can point toward ostensible remedies that don’t in fact help to remedy the problem.
The irony is that the problem is actually more mundane than the continuing existence of racial animus, and the fixes aren’t really all that complicated. A good swath of the literature suggests that greater attention to individual qualifications—that is, providing enough time and the platforms actually to notice individual qualifications—would be a big step toward remedying the problem. And that’s something both whites and blacks, both liberals and conservatives, can get behind.