Resources on Unconscious Bias
Unconscious bias—also known as implicit social cognition—refers to thoughts and feelings that are outside of conscious awareness and control. Although we all would like to believe that we are objective and capable of judging people solely on the basis of merit, over 20 years of research demonstrates that we generally fall short of our self-perceptions (see, e.g., Banaji et al (2003)). There is a vast literature on unconscious bias. This page provides links to some online resources, a list of suggested strategies for minimizing bias in faculty recruitment, and a selected list of academic studies and other articles on the topic.
You may also download and print our one-page tip sheet, Research Supporting the Existence of Unconscious Bias and its Effects on Diversity in Recruitment.
- Implicit Association Test. Project Implicit is a non-profit organization founded by researchers from the University of Washington, Harvard University, and the University of Virginia. Its goal is to educate the public about hidden biases and to function as a virtual laboratory for collecting data on unconscious bias. The link takes you to a page where you can take online implicit association tests (IATs) relating to different types of unconscious bias, including skin-tone preference, sexuality preference, the link between gender and science, age preference, the link between gender and family versus career, racial preference, weight preference, disability preference, and others. For an analysis of issues relating to IAT procedures and application, see Nosek et al (2005).
- Managing Unconscious Bias workshop. Facebook recorded its internal training program on managing unconscious bias and has made the videos available to the public. The link provides access to the video presentation, which is divided into six brief modules. Presentation slides and a bibliography of reference materials are also available for download.
- Interrupting Bias in the Faculty Search Process. The University of Washington’s ADVANCE Center for Institutional Change created a training video and facilitation guide to help faculty search committees uncover and address unconscious bias in the faculty candidate evaluation process.
Strategies for Minimizing the Impact of Bias in Recruitment
Set forth below is a list of specific interventions for addressing unconscious bias in the context of faculty recruitment. The strategies, adapted principally from WISELI's Searching for Excellence and Diversity® Guide (see pages 52-60), are grounded in research, including the studies listed in the bibliography below. All of these strategies are also reflected in the Faculty Search Guidelines.
- Set ground rules for search committee meetings (e.g.: no interrupting other committee members).
- In advance of a search, facilitate structured discussions around the academic criteria for evaluating candidates so that the search committee has a unified conception of what criteria to use, how to weigh them, and how to measure quality within a given domain.
- Use structured evaluation templates for reviewing applications, job talk evaluations, and one-on-one interviews. These templates should include both quantitative rankings of job-relevant criteria and qualitative written information. For quantitative rankings, forms should provide instruction about what type of behavior/achievement corresponds to each level of score.
- Spend sufficient time evaluating each applicant, and minimize distractions when reviewing applicant materials.
- Familiarize yourself with the literature on unconscious bias (see bibliography below).
- Be aware of your own potential biases.
- Encourage others to call out incidents of bias.
- Use inclusion rather than exclusion strategies in making selection decisions (e.g.: include for further consideration those applicants the search committee deems to be qualified as opposed to excluding those it deems to be unqualified).
- Agree in advance on a set of interview questions that will be asked of each candidate (see also Appendix F - Legal Considerations in the Faculty Search Guidelines).
- Be prepared to defend each decision to advance or eliminate a candidate.
Selected Studies and Other Articles on Unconscious Bias
(access to most of the links provided below requires a Northwestern University NetID and Password)
Studies of Biases in Academia
- Maliniak, D., Powers, R. & Walter, B. F. (2013). The gender citation gap in international relations. International Organization, 67(4), 889-922.
- Milkman, K. L., Akinola, M. & Chugh, D. (2012). Temporal distance and discrimination: an audit study in academia. Psychological Science, 23(7), 710-717.
- Moss-Racusin, C. A., Dovidio, J. F., Brescoll, V. L., Graham, M. J. & Handelsman, J. (2012). Science faculty’s subtle gender biases favor male students. Proceedings of the National Academy of Sciences, 109(41), 16474-16479.
- Perna, L. W. (2001). Sex and race differences in faculty tenure and promotion. Research in Higher Education, 42(5), 541-567.
- Perna, L. W. (2005). Sex differences in faculty tenure and promotion: The contribution of family ties. Research in Higher Education, 46(3), 277-307.
- Steinpreis, R. E., Anders, K. A., & Ritzke, D. (1999). The impact of gender on the review of curricula vitae of job applicants and tenure candidates: A national empirical study. Sex Roles, 41(7/8), 509-528.
- Trix, F. & Psenka, C. (2003). Exploring the color of glass: Letters of recommendation for female and male medical faculty. Discourse & Society, 14(2), 191-220.
- Wennerås, C. & Wold, A. (1997). Nepotism and sexism in peer-review. Nature, 387, 341-343.
Studies of Biases Relevant to Personnel Decisions
- Bertrand, M. & Mullainathan, S. (2004). Are Emily and Greg more employable than Lakisha and Jamal? A field experiment on labor market discrimination. American Economic Review, 94(4), 991-1013.
- Biernat, M. & Fuegen, K. (2001). Shifting standards and the evaluation of competence: Complexity in gender-based judgment and decision making. Journal of Social Issues, 57(4), 707-724.
- Devine, P. G., Plant, E. A., Amodio, D. M., Harmon-Jones, E., & Vance, S. L. (2002). The regulation of explicit and implicit race bias: The role of motivations to respond without prejudice. Journal of Personality and Social Psychology, 82(5), 835-848.
- Dovidio, J. F. & Gaertner, S. L. (2000). Aversive racism and selection decisions: 1989 and 1999. Psychological Science, 11(4), 315-319.
- Eagly, A. H. & Karau, S. J. (2002). Role congruity theory of prejudice toward female leaders. Psychological Review, 109(3), 573-598.
- Goldin, C. & Rouse, C. (2000). Orchestrating impartiality: The impact of “blind” auditions on female musicians. American Economic Review, 90(4), 715-741.
- Hugenberg, K., Bodenhausen, G. V., & McLain, M. (2006). Framing discrimination: Effects of inclusion versus exclusion mind-sets on stereotypic judgments. Journal of Personality and Social Psychology 91(6), 1020-1031.
- Rivera, L. A. (2012). Diversity within reach: Recruitment versus hiring in elite firms. ANNALS of the American Academy of Political and Social Science, 639, 71-90.
- Rivera, L. A. (2015). Go with your gut: Emotion and evaluation in job interviews. American Journal of Sociology, 120(5), 1339-1389.
- Uhlmann, E. L. & Cohen, G. L. (2005). Constructed criteria: Redefining merit to justify discrimination. Psychological Science 16(6), 474-480.
- Banaji, M. R., Bazerman, M. H., & Chugh, D. (2003). How (un)ethical are you? Harvard Business Review 81(12), 56-64.
- Connolly, M. R., Lee, Y. G., & Savoy, J. N. (2015). Faculty hiring and tenure by sex and race: New evidence from a national survey. Unpublished manuscript, Wisconsin Center for Education Research, University of Wisconsin-Madison, Madison WI.
- Nosek, B. A., Greenwald, A. G., & Banaji, M. R. (2005). Understanding and using the Implicit Association Test: II. Method variables and construct validity. Personality and Social Psychology Bulletin 31(2), 166-180.
- Rivera, L. (2015, June 15). Were you judged fairly at your last job interview? Fortune.
- Williams, J. C. & Bornstein, S. (2008). The evolution of “FReD”: Family responsibilities discrimination and developments in the law of stereotyping and implicit bias. Hastings Law Journal 59(6), 1311-1358.