re:Work - Guide: Raise awareness about unconscious bias
Learning the science and hosting a workshop can help you understand the impact of unconscious bias and begin unbiasing.

One of the first steps towards unbiasing is education. External research shows that awareness of unconscious bias can lead to reversals in biased outcomes, and understanding of the unconscious biases that underlie beliefs may be necessary for changing attitudes.

In 2013, Google began educating employees and leaders en masse - creating Unconscious Bias @ Work and other tools - to start a conversation about unbiasing. This helped ensure that employees had a common understanding and language to talk about unconscious bias, and the platform to do so.

By understanding the science of unconscious bias you will be better equipped to talk about it (especially with skeptics) and tackle it within your organization. New research continues to be published on this topic so make sure to stay up to date on the science. Here’s a primer:

  1. Banaji, M. R., Caruso, E. M. & Rahnev, D. A. (2009). Using Conjoint Analysis to Detect Discrimination: Revealing Covert Preferences from Overt Choices.
  2. Brooks, A. W., Huang, L., Kearney, S. W., & Murray, F. E. (2014). Investors Prefer Entrepreneurial Ventures Pitched by Attractive Men.
  3. Bongiorno, R., Haslam, A. S., Hersby, M. D., & Ryan, M. K. (2011). Think Crisis–Think Female: The Glass Cliff and Contextual Variation in the Think Manager–Think Male Stereotype.
  4. Brescoll, V. L., Dovidio, J. F., Graham, M. J., Handelsman, M. J. & Moss-Racusin C. A. (2012). Science Faculty’s Subtle Gender Biases Favor Male Students.
  5. Hebl, M. R., Foster, J. B., Mannix, L. M., & Dovidio, J. F. (2002). Formal and Interpersonal Discrimination: A Field Study of Bias Toward Homosexual Applicants.
  6. Jones, K. P., Peddie, C. I., Gilrane, V. L., King, E. B., & Gray, A. L. (2013). Not So Subtle: A Meta-Analytic Investigation of the Correlates of Subtle and Overt Discrimination.
  7. Martell, R. F., Lane, D. M., & Emrich, C., (1996). Male-Female Differences: a Computer Simulation.
  8. Murphy, M. C., Steele, C. M., & Gross, J. J. (2007). Signaling Threat: How Situational Cues Affect Women in Math, Science & Engineering Settings.
  9. Rudman, L. A., Ashmore, R. D., & Gary, M. L. (2001). “Unlearning” Automatic Biases: The Malleability of Implicit Prejudice and Stereotypes.
  10. Welle, B., & Heilman, M. E. (2007). Formal and Informal Discrimination against Women at Work: The Role of Gender Stereotypes.