Implicit Bias Series: Topic Intro | Part 1 | Part 2 | Part 3
Implicit Bias Series
Part 2:
Creating Awareness and Reducing Implicit Biases
Overview
Our implicit cognition matters for our students, and so by its unconscious nature, it is a challenge to recognize and measure.Many are generally weak at introspection, so, unsurprisingly, we are often unaware of our biases. Even when aware, research shows that self-reports of bias are both unreliable (Greenwald & Banaji, 2007) and often influenced by social desirability concerns (Amodio & Devine, 2009; Dasgupta, 2013). With such restrictions, researchers developed assessments that employ multiple methods, ranging from physiological approaches to priming methods to response latency measures (Kirwan Institute, 2015).
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Recognize Your Own Implicit Biases
To interrogate your own implicit biases is to explore free tools developed by Harvard University’s “Project Implicit.” The Implicit Association Test (IAT) is one accessible method that measures associations between photos and words, conditional on response times. These tests may reveal your own subconscious assumptions about students that might unintentionally influence the ways you interact with them. Despite ideological debates related to implicit bias, a significant body of research substantiates the validity and reliability of the IAT (J. Kang & Lang, 2010). Being aware of our biases is the first step towards reducing bias, but what strategies help us to realize this goal?
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Strategies to Reduce Implicit Biases
Given that implicit biases are socially conditioned, they are modifiable and can be unlearned. Much study has been dedicated to the process of debiasing, a term that researchers use to describe an approach to countering our existing biases. Debiasing works through deliberate and focused construction of new mental associations sustained over time (Devine, 1989). With repetition and training, research shows the newly learned implicit associations can stabilize (Glock & Kovacs, 2013).
Evidence suggests that the following strategies have particular potential for success:
- Education efforts aimed at creating awareness of our biases, such as those already underway in the fields of criminal justice and health care (Kirwan, 2015)
- Counter-stereotypic (stereotype replacement) training, when individuals are trained to create new associations through visual or verbal signals (Devine et al., 2012; J. Kang et al., 2012)
- Exposure to counter-stereotypic individuals, whereby new associations are built when individuals are exposed to counter-stereotypic images such as male nurses or female scientists (Devine et al., 2012; Dasgupta & Asgari, 2004)
- Perspective taking, when individuals consider alternative viewpoints and recognize a diversity of perspectives (Devine et al., 2012; Benforado & Hanson, 2008)
- In-group and out-group contact, where members of both groups are brought together in cooperative, rather than competitive, environments. Such intergroup contact tends to reduce intergroup prejudice (Devine et al., 2012; Peruche & Plant, 2006).
Underpinning all these strategies is awareness. Recognizing the implicit biases about your own students and understanding some basics about debiasing are essential first steps in creating an inclusive environment. Part 3 of the series describes practical ways to integrate some of these techniques into instructional practice.
- Additional Resources
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- For resources to counter bias (and links to videos for students) from University of Michigan, visit this site
- For UC Berkeley’s Implicit Bias series, visit this site
- For more debiasing techniques, visit this site
- Citation
- Center for Educational Effectiveness [CEE]. (2019). Implicit bias series. Just-in-Time Teaching Resources. Retrieved from http://cee.ucdavis.edu/JITT
- References
- Amodio, D. M., & Devine, P. G. (2009). On the interpersonal functions of implicit stereotyping and evaluative race bias: Insights from social neuroscience. In R. E. Petty, R. H. Fazio, & P. Brinol (Eds.), Attitudes: Insights from the new implicit measures (pp. 193–226). New York, NY: Psychology Press.
Banaji, M. R., & Greenwald, A. G. (2013). Blindspot: Hidden biases of good people. New York, NY: Delacorte Press.
Benforado, A., & Hanson, J. (2008). The great attributional divide: How divergent views of human behavior are shaping legal policy. Emory Law Journal, 57(2), 311–408.
Dasgupta, N. (2013). Implicit attitudes and beliefs adapt to situations: A decade of research on the malleability of implicit prejudice, stereotypes, and the self-concept. Advances in Experimental Social Psychology, 47, 233–279.
Dasgupta, N., & Asgari, S. (2004). Seeing is believing: Exposure to counter-stereotypic women leaders and its effect on the malleability of automatic gender stereotyping. Journal of Experimental Social Psychology, 40(5), 642–658.
Devine, P. G. (1989). Stereotypes and prejudice: Their automatic and controlled components. Journal of Personality and Social Psychology, 56(1), 5–18.
Devine, P. G., Forscher, P. S., Austin, A. J., & Cox, W. (2012). Long-term reduction in implicit race bias: A prejudice habit-breaking intervention. Journal of Experimental Social Psychology, 46(8), 1267–1278.
Glock, S., & Kovacs, C. (2013). Educational psychology: Using insights from implicit attitude measures. Educational Psychology Review, 25(4), 503–522.
Kirwan Institute. (2015). State of the science: Implicit bias review.
Kang, J., Bennett, M., Carbado, D., Casey, P., Dasgupta, N., Faigman, D., & Mnookin, J. (2012). Implicit bias in the courtroom. UCLA Law Review, 59(5), 1124–1186.
Kang, J., & Lane, K. (2010). Seeing through colorblindness: Implicit bias and the law. UCLA Law Review, 58(2), 465–520.
Peruche, B. M., & Plant, E. A. (2006). The correlates of law enforcement officers’ automatic and controlled race-based responses to criminal suspects. Basic and Applied Social Psychology, 28(2), 193–199.