Inequities Exist but They’re Explained by Explicit Bias

Research into implicit bias has been driven partly by widespread declines in overt racism and sexism. However, particularly since the election of President Trump, the growth of far-right political movements in Europe, and the #MeToo movement, some critics have suggested that the historical turn to less overt forms of bias has been overstated. We don’t need implicit bias to explain contemporary discrimination and inequality, some critics say, as explicit bias can do the explaining. For example, Jesse Singal (2017) points to the Justice Department’s report that the Ferguson police and court officials engaged in widespread intentional race-based discrimination. He writes, “It might be advantageous to various people to say implicit bias rather than explicit bias is the most important thing to focus on, but that doesn’t make it true —a point driven home, perhaps, by the fact that the United States just elected one of the more explicitly racist presidential candidates in recent history” (2017).


Explicit bias undoubtedly plays a causal role in explaining outrageous discriminatory practices like those in Ferguson. It is also true that researchers

Skepticism About Bias 63 (including me) have sometimes been too quick to suggest that explicit racism and sexism are mostly old-fashioned and that implicit bias is the contemporary face of prejudice. And, as I said above, research on implicit bias has been overhyped by some, and to the extent that anyone has claimed that implicit bias is the most important cause of contemporary discrimination and inequality, Singal is right to disagree. However, the criticisms described above are overstated and misleading.

First, many researchers suggest that implicit bias is important to address within the large segment of the population that disavows prejudice and common social stereotypes. 1 suspect, for example, that the majority of readers of this volume oppose explicit discrimination. The fact that intentional discrimination is a pervasive and still-contemporary problem does not obviate the fact that there are many people who are explicitly opposed to discrimination, and who are aiming to be unbiased, and yet are susceptible to the kinds of biased behavior implicit bias researchers have been concerned about. The persistence of intentional discrimination, in other words, is no reason to abandon the research program focused on implicit bias.

Second, some critics elide the extensive and ongoing debate in the literature about the nature and relationship between implicit and explicit mental states, processes, and biases. “Implicit bias” is a term of art that refers to a set of unendorsed or disavowed behaviors, such as one’s performance on an IAT. Implicit measures, such as the IAT, are tests that quantify implicit bias. These tests have psychological causes, which are a combination of implicit and explicit processes (or implicit and explicit attitudes, depending on your preferred theory), as well as other features of cognition (e.g., the ability to control one’s impulses). In arguing that implicit bias is a confused notion because explicit biases are more significant causes of discriminatory behavior, Hermanson and others appear to be confusing mental processes with behavioral outcomes. By definition, implicit bias is disavowed behavior. Moreover, there is a rich, long-standing, and ongoing literature exploring the interactions of implicit and explicit processes that give rise to implicit bias. For example, researchers have known for some time that the best way to predict a person’s scores on an implicit measure like the IAT is to ask them their opinions about the IAT’s targets. Recent data have also demonstrated that people are fairly good at predicting their own IAT scores (Hahn et al. 2014). This doesn’t suggest that implicit bias is a meaningless construct. Rather, it suggests that measures of implicit bias are not “process pure” (i.e., what they measure is a mix of various cognitive and affective processes). By analogy, you are likely to find that people who say that cilantro is disgusting are likely to have aversive reactions to it, but this doesn’t mean that their aversive reactions are an invalid construct. Indeed, one of the leading theories of the dynamics and processes of implicit social cognition since 2006—Gawronski and Bodenhau-sen’s “Associative-Propositional Evaluation” model (APE, updated, e.g., in 2014; see Johnson, Chapter 1, “The Psychology of Bias: From Data to Theory”)—is based on a set of predictions about this process impurity (i.e., about the interactions of implicit and explicit evaluative processes).

That said, there are crucial open questions in the literature, and some forms of confusion are the responsibility of problematic theories. Arguably the most advertised and influential account of implicit bias posits attitudes that are outside of agents’ awareness and control. This definition is thrice problematic, as research suggests that we are not that unaware of our implicit biases (op cit.; according to APE, people fail to report their implicit biases not because they are unaware of them but because they reject them, either because they think they are unjustified or they want to appear unbiased); that there are many techniques available for gaining some degree of control over them (see Lai et al. 2013 for review); and that people don’t have “dual” attitudes that exist in isolation from one another. But, of course, there are many alternatives to this definition, from APE (op cit.) to my own (Brownstein and Madva 2012; Madva and Brownstein 2018; Brownstein 2018). The lively debate about how to characterize the construct of interest is ongoing, as it should be.

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