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Research Articles

Using a Virtual Workplace Environment to Reduce Implicit Gender Bias

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Pages 529-545 | Received 27 May 2021, Accepted 10 Feb 2022, Published online: 19 Apr 2022
 

Abstract

Implicit gender bias has costly and complex consequences for women in the workplace, with many women reporting gender microaggressions which result in them being overlooked or disrespected. We present an online desktop virtual environment that follows the story of a male or female self-avatar from the first-person perspective, who either experiences a positive or negative workplace scenario. The negative scenario included many examples from the taxonomy of gender microaggressions. Participants who experienced negative workplace experiences with a female self-avatar had significantly decreased levels of implicit gender bias compared to those who had a male self-avatar. There was evidence of empathy and perspective taking in the negative condition for the female self-avatar. Experiences of a positive workplace scenario showed no significant decreases in implicit gender bias regardless of self-avatar gender. We discuss the implications of these findings and make recommendations for virtual environment technologies and scenarios with respect to the reduction of implicit biases.

Acknowledgements

We thank the volunteers who lent their voices to the avatars and our online participants.

Notes

1 For the purposes of this paper, the term virtual environment (VE) includes fully immersive virtual environments as well as desktop virtual environments.

5 A positive ΔIAT indicates an increase in implicit gender bias. A negative ΔIAT indicates a decrease in implicit gender bias.

13 The taxonomy of a movie like Clouds Over Sidra is not clear. It is footage of the real world with a 360° camera. It is classified as a VR film by IMDB.

14 Cited from supplementary video (Cogburn et al., Citation2018).

Additional information

Funding

This work was funded by Craig Newmark Philanthropies and the Faculty Development Fund from the University of San Francisco.

Notes on contributors

Kevin Beltran

Kevin Beltran is a Software Engineer for Downpour Interactive, and specializes in Virtual Reality app development. He holds a BS in Computer Science from the University of San Francisco.

Cody Rowland

Cody Rowland is a software engineer at Downpour Interactive. Prior to his current position he was a student and research assistant at the University of San Francisco.

Nicki Hashemi

Nicki Hashemi is an undergraduate student pursuing Computer Science at the University of San Francisco. She has an interest in virtual reality and making a social impact through technology.

Anh Nguyen

Anh Nguyen is a graduate student in the Computer Science department at University of San Francisco. Her study spans Data Structure and Algorithms, Systems Programming and Software Development. She has an interest in Virtual Reality as well as Machine Learning and Artificial Intelligence. She interned at Ripple in summer 2021.

Lane Harrison

Lane Harrison is an Associate Professor of Computer Science at Worcester Polytechnic Institute. He obtained his PhD from the University of North Carolina at Charlotte. His research focuses on Information Visualization.

Sophie J. Engle

Sophie Engle is an Associate Professor at the University of San Francisco. She holds a PhD in Computer Science from the University of California, Davis, where her research focused on cybersecurity. Her current research interests include data visualization and computer science education.

Beste F. Yuksel

Beste F. Yuksel is an Assistant Professor of Computer Science at the University of San Francisco. She holds a PhD in Computer Science from Tufts University. Her research has won awards in the fields of brain-computer interfaces and virtual reality.

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