Of all the things people think about when moving to a new city, their likelihood of becoming more biased is not one of them. Maybe it should be.

Implicit biases—the immediate inferences we all make about other people—can inadvertently result in discrimination, even by those of us who are motivated to treat others fairly and equally. And these automatic biases can have negative consequences. For example, in places where the average implicit bias against Black individuals is high, Black infants suffer worse health at birth than White infants. In those places too, police are more likely to disproportionately use lethal force against Black citizens.

How can we combat implicit biases? Researchers who have searched for the answer to this question have made a critical assumption, leading some of them to conclude that implicit bias cannot be changed. The assumption is this: Implicit bias is a characteristic of the person, something like a personality trait. In this view, some people are inherently more implicitly biased than others, so it makes sense to focus on designing trainings or “interventions” that could reduce people’s biases.   

That is exactly what a large group of researchers attempted to do in a collaborative effort that tested nine interventions designed to reduce implicit bias across 18 university campuses.  Their research found that all of the interventions reduced implicit bias immediately, but the effect did not last even a few days. They concluded that implicit bias is a stable feature of the person that is difficult to change.

But what if implicit bias is not a characteristic of individual people, but rather of the places where they live? We automatically make certain inferences about the people in various social groups because we have knowledge of the stereotypes in our culture. However, some places are more likely to remind us of those stereotypes than other places.

In particular, places that have more social inequalities are more likely to reinforce negative stereotypes. Automatically associating “Black” with “poor,” for example, is more likely to occur in cities where economic racial disparities are obvious due to high levels of segregation and high poverty rates among Black individuals. So people who live in places that perpetuate racial disparities through unfair policies and unequal access to resources (often called “structural racism”) are more likely to encounter situations that cue these stereotypic associations.

However, any given person has many different experiences and social encounters from day to day, and these experiences may cause people’s automatic, stereotypic associations—and biases—to fluctuate. Although someone might score high on implicit bias one day, he or she might not the next. However, when you take the average implicit bias of all the people living in a certain place, then you get a sense of the true level of bias in that location.  

We call this phenomenon the “Bias of Crowds” because it is conceptually similar to the “wisdom of crowds,” which refers to the fact that averaging the collective knowledge of several people is more likely to yield the true answer than surveying any one individual in that group. With the Bias of Crowds theory in mind, we re-analyzed the data from the large intervention study that was conducted across 18 university campuses. The researchers who conducted that study assumed that because the average reduction in implicit bias disappeared a few days after the interventions, individuals’ implicit biases had returned to their original levels. When we looked at the data, though, we found that this was not the case.

A few days after receiving the intervention to reduce implicit bias, individuals’ levels of implicit bias had changed mostly randomly—some people’s bias went up, some people’s went down, and some were largely unchanged—but these changes didn’t have much to do with people’s original level of bias.

However, when we looked at the average implicit bias on any given campus, those scores did return to similar levels as before the interventions took place. But we also found that campuses that displayed a confederate monument, had less faculty diversity, or had less economic mobility among students were more likely to have higher average levels of implicit bias. These campus characteristics potentially acted as visible reminders of racial stereotypes and activated a stronger wave of biases on some campuses than on others.

So how can we combat implicit bias? Our results suggest that places are stubbornly biased and can contribute to the bias of individual people. Restructuring the places where we live to be more inclusive, equitable, and welcoming of diversity might be a first, and longer-lasting, way to reduce implicit bias than interventions aimed at individual people. The results imply that the effort cannot be concentrated on a few “biased people” and set aside. To change a place requires shared social commitment, ongoing and active effort, and tangible investment. In the case of college campuses, for example, removing confederate monuments and increasing the diversity of the faculty are concrete steps that may effectively weaken the collective bias that, at first, seemed so resistant to change.

If we are more likely to be biased at certain places, then it is time to start thinking about trying to change not just people’s minds, but also their surroundings.


For Further Reading:

Lai, C. K., Skinner, A. L., Cooley, E., Murrar, S., Brauer, M., Devos, T., . . . Nosek, B. A. (2016). Reducing implicit racial preferences: II. Intervention effectiveness across time. Journal of Experimental Psychology: General, 145, 1001–1016. doi:10.1037/xge0000179

Payne, B. K., Vuletich, H. A., Lundberg, K. B. (2017). The bias of crowds: How implicit bias bridges personal and systemic prejudice. Psychological Inquiry, 28, 233–248. doi:10.1080/1047840X.2017.1335568

Vuletich, H. A., & Payne, B. K. (2019). Stability and Change in Implicit Bias. Psychological Science, 30(6), 854–862. https://doi.org/10.1177/0956797619844270

 

Heidi A. Vuletich is a social and developmental psychologist who studies how social and economic inequalities affect people’s perceptions of themselves and others.