Unconscious Biases
The term “bias” (also “implicit bias” and “unconscious bias”) refers to the unconscious assumptions, beliefs, attitudes and stereotypes that human brains have about different groups. These learned mental short-cuts affect how we perceive and respond to people.
Some key features about unconscious biases:
- Everyone has them
- They can be activated within a fraction of a second
- We can hold biases against our own group
- We can hold biases that go against our stated beliefs
- Biases are generally shared within social groups, though people also have biases favouring people who share their identities
- Biases are persistent, but can be changed with attention and work
Unconscious biases prevent us from seeing fairly and accurately the information or the people in front of us. Much research shows that unconscious biases systematically disadvantage already disadvantaged people, and provide un-earned advantages to those already advantaged. As a result of these impacts, unconscious biases negatively affect our ability to identify and hire the best candidates.
At UVic, we are working to increase understanding of the actions and impacts of unconscious biases, and to establish processes and education that will reduce their impact within all stages of employment.
Training materials on unconscious bias
- 5 Tips on Checking your Biases with Dr. Paweena Sukhawathanakul: https://www.youtube.com/watch?v=b5ixEl5rAHo
- Canadian Society for Chemistry: Video on bias for award selection committees https://www.youtube.com/watch?v=cmSG3iPKqi8
- Canadian Institutes of Health Research (CIHR): Online training on unconscious biases (same as CRC training) http://www.cihr-irsc.gc.ca/lms/e/bias/
- Canada Research Chairs (CRC): Online training on unconscious biases (same as CIHR training) http://www.chairs-chaires.gc.ca/program-programme/equity-equite/bias/module-eng.aspx?pedisable=false
- Project Implicit: Online tests to identify unconscious biases https://implicit.harvard.edu/implicit/
Online resources
- Gender decoder: identifying gender-coding in job ads
- Gendered Language in Teacher Reviews: Interactive chart
- Tips: Avoiding gender bias in in reference writing
- Cognitive bias codex: Every single cognitive bias in a chart
- CDO Insights: Proven strategies for addressing unconscious bias in the workplace. http://www.cookross.com/docs/UnconsciousBias.pdf
Some studies on unconscious bias
- Association of American Medical Colleges (2009). Unconscious bias in faculty and leadership recruitment. https://www.aamc.org/download/102364/data/aibvol9no2.pdf
- Duch, J., et al. (2012). The Possible Role of Resource Requirements and Academic Career-Choice Risk on Gender Differences in Publication Rate and Impact. PLOS One 7(12), e51332. https://arxiv.org/abs/1212.3320
- Hekman, D. R., Johnson, S. K., Maw-Der Foo, & Wei Yang. (2017). Does Diversity-Valuing Behavior Result in Diminished Performance Ratings for Non-White and Female Leaders? Academy of Management Journal, 60(2), 771–797. https://doi.org/10.5465/amj.2014.0538
- Milkman, K. L., Akinola, M., & Chugh, D. (2015). What happens before? A field experiment exploring how pay and representation differentially shape bias on the pathway into organizations. Journal of Applied Psychology, 100(6), 1678-1712. http://dx.doi.org/10.1037/apl0000022 and http://psycnet.apa.org/record/2015-15680-001?doi=1
- O’Meara et al. (2017). Asked More Often: Gender Differences in Faculty Workload in Research Universities and the Work Interactions That Shape Them. American Educational Research Journal 54(6), pp. 1154-1186. https://doi.org/10.3102/0002831217716767
- Powell, K. (2018). These labs are remarkably diverse — here’s why they’re winning at science. Nature, June 6, 2018. https://www.nature.com/articles/d41586-018-05316-5
- Sensoy, Özlem & Robin DiAngelo (2017) “We Are All for Diversity, but . . .”: How Faculty Hiring Committees Reproduce Whiteness and Practical Suggestions for How They Can Change. Harvard Educational Review. 87(4), pp. 557-580. http://tinyurl.com/ybxaj2ov and https://hepgjournals.org/doi/10.17763/1943-5045-87.4.557
- Sheltzer, J.M. & Smith, J.C. (2014). Elite male faculty in the life sciences employ fewer women. Proceedings of the National Academy of Sciences of the United States of America, 111(28), pp. 10107-10112. https://doi.org/10.1073/pnas.1403334111
- Witteman, H.O., et al. (2019). Are gender gaps due to evaluations of the applicant or the science? A natural experiment at a national funding agency (2019). The Lancet, 393(10171), pp. 531-540. https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(18)32611-4/fulltext and https://doi.org/10.1016/S0140-6736(18)32611-4