Update: For more information on this topic, read the new Eos article “Getting to Fair: Recognizing Implicit Bias and Easing Its Impact,” co-authored by Mary Anne Holmes.  Mary Anne Holmes is also featured this month as the Paths Through Science profile at the AGU Career Center.

The first time I heard the term implicit bias and learned what it was, I was with several other women scientists and we all had a face-palm moment, “So that’s what has been wrong all this time! This is why we feel unheard in our meetings and committees, why we needed a better CV than our male counterparts to get a job.”

Implicit biases are unconscious biases shared within a given culture that aren’t knowingly held or recognized. Implicit assumptions are unaddressed ideas a society has about the way the world and the people in it function. It’s a necessary way for our brains to process information and avoid overload. We learn these assumptions by seeing situations happen the same way repeatedly and accepting it as a norm, so when the same or similar situations arise, we don’t have to think too hard. These assumptions become bias when they lead to actions that have a negative impact on a person or whole group.

The key note about implicit bias is this: within a given culture, people share the same biases. For example, if every doctor I’ve ever seen is male, when someone says, “I’m going to my doctor today,” I picture a man in the examination room the same way I would picture a woman if they are going to see a nurse. Most men and women will have the same picture.

However, these biases can be hazardous in the STEM workforce because both men and women scientists initially picture a male when we hear the word scientist.

This is demonstrated by research such as Moss-Racusin and co-authors’ 2012 National Academies paper, where they learned both sexes were more likely to offer a job to a male lab assistant applicant rather than a woman, and both men and women offered a higher starting salary to the male applicant.

Implicit assumptions and biases kick in especially when we are in a rush and need to make a quick decision. “A pile of applications for graduate admissions? Ah, this student and this student come from institutions I know, worked with people I know and enjoy – I’ll let them in. These others, I don’t know; maybe next time.” This situation is common and decision makers may not even realize that the institution/colleague triggered a positive impression and assumption of the applicants.

We all have implicit assumptions, some of which tip over into bias by assuming someone can or can’t do a job because of gender, sexual orientation, national origin, socio-economic status, race, ethnicity, etc. The challenge, for not just employers but the public, is to first become aware of these unconscious biases, then try to minimize the impact.

To learn more about implicit biases, their effects and manifestations, I’d recommend utilizing reference apps (e.g. Google Scholar) to explore the literature and popular books such as Blind Spot by Benaji and Greenwald, Blink by Malcom Gladwell, and Hidden Brain by Shankar Vedantam, as well as his homonymous podcast. You can even take the Implicit Association Test (IAT) online and see for yourself where your biases might lay.

Mary Anne Holmes is a Professor Emerita at the University of Nebraska-Lincoln and previously served as Program Director for ADVANCE, an NSF initiative dedicated to increasing female participation in Science Careers. Holmes has dedicated much of her professional life and research to general equality and female plight in the geosciences.

Citation:

Moss-Racusin, C.A., Dovidio, J.F., Brescoll, V.L., Graham, M.J. and Handelsman, J., 2012. Science faculty’s subtle gender biases favor male students. Proceedings of the National Academy of Sciences, 109(41), pp.16474-16479.