What is unconscious bias?

Bias is a prejudice in favor of or against one thing, person, or group compared with another, usually in a way that’s considered to be unfair. Biases may be held by an individual, group, or institution and can have negative or positive consequences.

There are two types of biases:

  1. Conscious bias (also known as explicit bias)
  2. Unconscious bias (also known as implicit bias)

It is important to note that biases, conscious or unconscious, are not limited to ethnicity and race. Though racial bias and discrimination are well documented, biases may exist toward any social group. Age, gender, gender identity, physical/cognitive abilities, religion, sexual orientation, weight, and many other characteristics are subject to bias.

Unconscious biases are social stereotypes formed outside conscious awareness. Everyone holds unconscious beliefs about various social and identity groups, and these biases stem from the universal human tendency to organize the outside world (identify threats, assess safety) using category shortcuts.

Unconscious bias is far more prevalent than conscious prejudice and often does not match our conscious values and beliefs. Biases may be more likely to influence behavior when we are multi-tasking or working under stress and time pressure.

What is the influence of implicit/unconscious bias on patient care?

A growing body of evidence supports the role of unconscious bias on disparities in access to, and outcomes, of health care.

  • Unconscious biases develop at an early age: biases are measurable during middle childhood and appear to develop across childhood. [1]
  • Unconscious biases have real world effects on behavior. [2]
  • Unconscious biases are malleable; the impact of unconscious bias can be reduced through training. [3]

A substantial amount of research demonstrates the adverse impact of unconscious bias in the criminal justice system, education, as well as health/health care. [4]

Conscious and unconscious bias has an impact on hiring, promotion, and mentoring, and contributes to health care disparities.

For example:

  • Fictitious resumes with White-sounding names sent to help-wanted ads were more likely to receive callbacks for interviews compared to resumes with African-American sounding names. Resumes with White-sounding names received 50% more callbacks for interviews. [5]
  • Science faculty rated male applicants for a laboratory manager position as significantly more competent and hirable than female applicants. Faculty also selected a higher starting salary and offered more career mentoring to the male applicants. [6]
  • Implicit bias among health care professionals can influence their behaviors and judgments. [7]

How is implicit bias assessed?

Of the tools available, the Implicit Association Test (IAT) is most well-studied. The IAT was developed to detect unconscious bias in race, gender, sexual orientation, and national origin.

How does the IAT work?

The IAT measures the relative strength of associations between pairs of concepts. It is designed as a sorting task in which individuals are asked to sort images or words that appear on a computer screen into one of two categories. The basic premise is that when two concepts are highly correlated in the unconscious (e.g., Asian people are smart), people are able to pair those concepts faster than two concepts that are not strongly associated (e.g., Asian people are lazy). The IAT is relatively resistant to social desirability concern, and the reliability and validity have been rigorously tested.

What does the IAT tell us about bias in health care?

The IAT has been used to explore the impact of unconscious bias on clinician behavior.

  • A greater pro-White unconscious bias among physicians is associated with greater likelihood of prescribing thrombolytics for White patients compared to Black patients presenting with the same acute coronary syndrome. [8]
  • A greater pro-White unconscious bias was associated with a greater willingness to prescribe pain medications for White versus Black children presenting with the same painful syndromes. [9]
  • Greater pro-White unconscious bias was associated with poorer ratings of the quality of interpersonal care among Black patients as compared to White patients. [10]

How can I reduce the impact of my unconscious bias?

Individual strategies to address unconscious bias include:

  • Promoting self-awareness: recognizing one’s biases using the Implicit Association Test (or other instruments to assess bias) is the first step. During patient care, ask yourself “Would I treat this patient any differently if he or she were White?”.
  • Understanding the universal nature of unconscious bias is essential. The categorization process that gives rise to unconscious bias is a normal and universal aspect of human cognition. Understanding this concept can help individuals gain conscious awareness of how unconscious biases influence our behaviors, and conscious awareness gives us the choice and ability to reduce its adverse impacts. [11]
  • Opportunities to interact with others (especially those from socially dissimilar groups) can be helpful in reducing stereotyping.
  • Facilitated discussions and training sessions promoting bias literacy utilizing the concepts and techniques above have been effective in minimizing bias. Evidence suggests that providing unconscious bias training for faculty members reduces the impact of bias in the health system workplace. [12]

Team Strategies [13]

  • Remember that bias is universal, but teams should normalize attempts to label and uncover bias. Design processes for bias mitigation in advance.
  • Create a team culture where “pausing” and checking for bias is the norm.
  • Hold yourself accountable before others, and engage in challenging team conversations regularly.

Institutional Strategies

Changes in individual behavior require a supportive work context through organizational structures and processes that recognize the reality and the power of unconscious bias and take steps to reduce it. This includes standardizing and routinizing equity and inclusion in staff and leadership recruitment, hiring, retention, performance rating, and promotion; to assess and work to improve the experience of diverse patient groups; and to train all staff in awareness of and steps to reduce the impact of unconscious bias on the care they provide. Examples include:

  • Developing concrete, objective, and standardized indicators and outcomes for hiring, evaluation, and promotion to reduce the influence of unconscious bias and stereotypes [14-16]
  • Developing standardized criteria for performance evaluations [17]
  • Developing and utilizing structured interviews, and developing objective evaluation criteria for hiring [18-19]
  • Providing unconscious bias training workshops for all staff and leadership

Learn More


  1. Dore RA, Hoffman KM, Lillard AS, Trawalter S. Children's racial bias in perceptions of others' pain. Brit J Dev Psychol. 2014;32(2):218–31.

  2. Dasgupta N. Implicit Ingroup Favoritism, Outgroup Favoritism, and Their Behavioral Manifestations. Social Justice Research. 2004;17(2), 143–169.

  3. Dasgupta N, Greenwald AG. On the malleability of automatic attitudes: combating automatic prejudice with images of admired and disliked individuals. J Pers Soc Psychol. 2001 Nov;81(5):800-14.

  4. State of the Science: Implicit Bias Review 2014. Kirwan Institute for the Study of Race and Ethnicity.

  5. Bertrand M, Mullainathan S. Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination. American Economic Review. 2004;94(4):991-1013.

  6. Moss-Racusin CA, Dovidio JF, Brescoll VL, Graham MJ, Handelsman J. Science faculty's subtle gender biases favor male students. Proc Natl Acad Sci USA. 2012 Oct 9;109(41):16474-9.

  7. Moskowitz G, Stone J, Childs A. Implicit Stereotyping and Medical Decisions: Unconscious Stereotype Activation in Practitioners' Thoughts About African Americans. American Journal of Public Health. 2012;102,996-1001.

  8. Green AR, Carney DR, Pallin DJ, et al. Implicit bias among physicians and its prediction of thrombolysis decisions for black and white patients. J Gen Intern Med. 2007;22(9):1231-1238.

  9. Sabin JA, Greenwald AG. The influence of implicit bias on treatment recommendations for 4 common pediatric conditions: pain, urinary tract infection, attention deficit hyperactivity disorder, and asthma. Am J Public Health. 2012 May;102(5):988-95.

  10. Cooper LA, Roter DL, Carson KA, Beach MC, Sabin JA, Greenwald AG, Inui TS. The associations of clinicians' implicit attitudes about race with medical visit communication and patient ratings of interpersonal care. Am J Public Health. 2012 May;102(5):979-87.

  11. Burgess D, van Ryn M, Dovidio J, Saha S. Reducing racial bias among health care providers: lessons from social-cognitive psychology. J Gen Intern Med. 2007;22(6):882-887.

  12. Carnes M, Devine PG, Isaac C, et al. Promoting Institutional Change Through Bias Literacy. J Divers High Educ. 2012;5(2):63-77.

  13. Halvorson H, Rock D. Beyond Bias. Strategy + Business. July 13, 2015. https://www.strategy-business.com/article/00345?gko=ed7d4

  14. Fiske ST, Taylor SE. McGraw-Hill Series in Social Psychology: Social Cognition (2nd ed.). Mcgraw-Hill Book Company, 1991.

  15. Heilman ME. Description and prescription: How gender stereotypes prevent women's ascent up the organizational ladder. Journal of Social Issues. 2001;57(4),657–674.

  16. Biernat M, Manis M. Shifting standards and stereotype-based judgments. Journal of Personality and Social Psychology. 1994;66(1), 5–20.

  17. Heilman ME, Haynes MC. No Credit Where Credit Is Due: Attributional Rationalization of Women's Success in Male-Female Teams. Journal of Applied Psychology. 2005;90(5),905–916.

  18. Martell RF, Guzzo RA. The dynamics of implicit theories of group performance: When and how do they operate? Organizational Behavior and Human Decision Processes. 1991;50(1), 51–74.

  19. Heilman ME. Description and prescription: How gender stereotypes prevent women's ascent up the organizational ladder. Journal of Social Issues. 2001;57(4),657–674.

Related Toolkits

Get the latest updates in your inbox!