Implicit Bias

 

There are two types of biases: explicit and implicit. Explicit bias is the bias you are aware of and implicit bias is unconscious bias. First coined in 1995, implicit bias refers to the attitudes or stereotypes that affect our understanding, actions, and decisions in an unconscious manner (Greenwald & Banaji, 1995).

If you are convinced that you do not have implicit bias – you wouldn’t know it – it is unconscious. In fact, this aspect makes it so difficult to self-identify. Implicit bias may run counter to your deeply held beliefs without you realizing it. It is quite possible that your explicit biases run contrary to your implicit biases, and you would not be aware of it.

 

How does this happen? 

There are two types of thinking (quick instinctive and slow/methodical) The former may help us identify patterns more quickly or even protect us from potential threats that may have helped us survive thousands of years ago, however it is still fallible.  It can also lead to many results that are dangerous and harmful (Kahneman (2011)).

How can implicit bias be harmful?  

Because it is unconscious, it can permeate all aspects of our society. This impedes notions of fairness or impartiality that will help promote the best people for jobs.

Studies have revealed that Implicit bias exists in our healthcare, legal system, workplace and everyday life.  Implicit bias in healthcare in the US contributes to women and racial minorities experiencing:

• less accurate diagnoses,
• curtailed treatment options,
• less pain management, and
• worse clinical outcomes

Moreover, the same implicit bias affects communication, collaboration, performance reviews, as well as promotions.

 

Implicit bias can show up in areas that you wouldn’t expect.

As it is undetected, it can undermine the success of institutions as well as being injurious to individuals. By unfairly biasing our choices, we are promoting unjust behavior that can impede success, such as in the sciences, because the best person for the job was not actually selected due to favoritism based on arbitrary qualities.

 

Research shows that when presented with identical resumes, various biases occur when changing one variable that is not relevant for selecting a job.  Having an ‘ethnic’ sounding name, or one that is more associated with a minority, will significantly decrease the chances of being selected to a position. (Klein, Rose & Waters, 2021) Even more surprising, is that when shown pictures revealing relative heights, the taller candidate will be greatly advantaged.  This advantage is so significant and consistent, that those under the average height are speculated to make more than $2000 less a year for every inch below average (Wang et al., 2020). Similar biases have been recorded for applicants BMI. Thus, many individuals are being denied equal opportunity while others are afforded positions that they may not even be as qualified for. Further, their promotion is heavily influenced by what Rawls’ (1971) would call “morally arbitrary properties”.

Luckily, there is hope. 

Orchestras used to be mostly composed of male musicians, even though admittance should be based on musical skill.  When auditions started using blind-review for musicians, there was a significant increase in female musicians being selected. A simple way to overcome this implicit bias was to add a curtain between the judges and the applicant.  Does this solve all problems of implicit bias? No. However, it shows that we can sometimes modify the process to help correct unfairness and minimally promote impartiality.

 

The first step in battling implicit bias is recognizing that it exists and you also have implicit biases.  Only then can we take steps to identify what they may be and how we can help ensure that these do not unfairly influence important decisions. While this is not easy, it is critical for promoting a more just and effective society where we can be better healthcare workers, police officers, teachers, as well as better people.

  

References

Bertrand, M., et al. (2005), Implicit Discrimination, 95 American Economic Review 94.

Bertrand, M & S Mullainathan (2004) Are Emily and Greg more employable than Lakisha and Jamal? A field experiment on labor market discrimination. American Economic Review 94:991-1013.

Chapman, E. N., Kaatz, A., & Carnes, M. (2013). Physicians and implicit bias: how doctors may unwittingly perpetuate health care disparities. Journal of general internal medicine, 28(11), 1504-1510.

Charlesworth, T. E., & Banaji, M. R. (2019). Patterns of implicit and explicit attitudes: I. Long-term change and stability from 2007 to 2016. Psychological science, 30(2), 174-192.

Glaser, J & E Knowles Implicit Motivation to Control Prejudice, 44 Journal of Experimental Social Psychology 164 (2008).

Goldin, C. & C Rouse. 2000. "Orchestrating Impartiality: The Impact of "Blind" Auditions on Female Musicians." American Economic Review, 90 (4): 715-741.

Green. A. et al. (2007), Implicit Bias Among Physicians and Its Prediction of Thrombolysis Decisions for Black and White Patients, 22 Journal of General Internal Medicine 1231.

Greenwald, A. G., & Banaji, M. R. (1995). Implicit social cognition: attitudes, self-esteem, and stereotypes. Psychological review, 102(1), 4.

Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. (1998). Measuring individual differences in implicit cognition: the implicit association test. Journal of personality and social psychology, 74(6), 1464.

Greenwald, A. G., & Krieger, L. H. (2006). Implicit bias: Scientific foundations. California Law Review, 94(4), 945-967.

Kahneman, D. (2011). Thinking, fast and slow. Macmillan.

Kline, P., Rose, E., & C. Walters (2021) Systemic Discrimination Among Large U.S. Employers University of Chicago, Becker Friedman Institute for Economics Working Paper No. 2021-94.

Osensky, T (2017) Shortchanged: Height Discrimination and Strategies for Social Change. ForeEdge: NH.

Rawls, J. (1971) A Theory of Justice. Harvard University Press. MA.

Wang J, Chen Q, Chen G, Li Y, Kong G, Zhu C (2020) What is creating the height premium? New evidence from a Mendelian randomization analysis in China. PLoS ONE 15(4): e0230555

Wigboldus, D. H., Sherman, J. W., Franzese, H. L., & A.V. Knippenberg (2004). Capacity and comprehension: Spontaneous stereotyping under cognitive load. Social Cognition, 22(3), 292-309.