Measuring Racial Avoidance on Virtual Streets

• In Event: Quantitative Study of Race & Gender

Abstract

In the United States and elsewhere, race is a salient feature of everyday social interactions. Though places of residence, work and study remain highly segregated along racial lines, with white Americans especially isolated from Black Americans, some degree of racial contact is particularly unavoidable in cities. Whether they occur on the street, on public transit or in other public spaces, these encounters need not involve conversation or verbal exchange to be impactful. Social scientists have long argued that Americans behave differently in the presence of racial out-group members than they do in encounters with their in-group, and in a way that reflects a torrid history of institutionalized racism and segregation.

One such behavior is racial avoidance. Using a novel field experiment and publicly available, real-time video feeds from New York City (NYC) Department of Transportation (NYC DOT) traffic cameras (https://nyctmc.org//), Dietrich and Sands (2023) find that, on average, pedestrians give a wider berth to Black confederates, as compared with white non-Hispanic confederates. The present study replicates this experiment within a Virtual Reality (VR) setting, ultimately allowing us to achieve two simultaneous ends.

First, Dietrich and Sands (2023) selected two NYC sidewalks based on census bloc data, with one sidewalk being more racially heterogenous than the other. However, once the video data was obtained, Dietrich and Sands (2023) found little statistical difference between them. Within the proposed VR experiment, the racial composition of the virtual sidewalk will be randomly varied, allowing a proper test of the “Neighborhood outgroup salience hypothesis” which states that pedestrians will give even a greater birth to black confederates in predominantly white neighborhoods.

Second, Dietrich and Sands (2023) were not able to test whether racial avoidance is associated with implicit racial bias. An Implicit Association Test (IAT) calibrated to detect racial bias and other well-tuned survey questions will be administered before participants take part in the VR experiment, giving some additional traction on this question. Building off prior work by Sands (17), we will also ask policy-related questions after the VR experiment to determine whether avoidance in VR has any ramifications on policy opinions.

The VR experiment itself was programmed by the Envision Center at Purdue. In the experiment, participants are randomly assigned either two phenotypically white or phenotypically black pedestrians who are engaged in a conversation on a sidewalk that mirrors one typically found in more affluent NYC neighborhoods. The virtual pedestrians were modeled from actual photos obtained from the Chicago Face Database (https://www.chicagofaces.org/). The racial composition of the neighborhood is also randomly assigned within the VR experiment. This was done by creating a background scene of a father walking across the street to meet his family who is sitting on a brownstone’s stoop.

Once the VR session begins, participants are asked to walk down the virtual sidewalk. To make the experience as realistic as possible, VR movement is controlled by actual movements within a large studio provided by the Envision Center. More specifically, participants are asked to physically walk around 25 feet while within the virtual environment. In doing so, they will walk past the virtual pedestrians, and we will measure the extent to which they avoid them.

In addition to building from our previous work, this study will also be the first social science study that utilizes VR in this way. Prior related VR work has not allowed participants to physically move within a virtual environment. Instead, participants either watch a video with a headset that allows them to look around or use a video game controller to move within a very confined space. Our experiment combines actual movements in a physical space with movements in VR, which allows us to precisely measure non-verbal behaviors, like avoidance. We think such an advance will serve as an important foundation for future work, as social scientists further explore the research possibilities provided by VR.

References

Dietrich, B.J., Sands, M.L. Seeing racial avoidance on New York City streets. Nat Hum Behav 7, 1275–1281 (2023). https://doi.org/10.1038/s41562-023-01589-7

Authors

• Bryce Dietrich, Purdue University

• Melissa Sands, London School of Economics