Although society has progressed toward equality, discrimination continues to play a role in the daily lives of minorities. At the time of the last census, non-white minorities comprised about one-fourth of the United States population [1].  Disparities in income, healthcare, and education persist for many of them [2][3]. Minimizing these disparities often involves political, legislative, and economic domains, but psychology and neuroscience also seek to understand and address these issues.

A major contributor to minority disparities may be implicit bias [4]. Implicit biases are learned, automatic ideas or preconceptions we hold without conscious awareness [5]. They differ substantially from explicit biases, which are our conscious beliefs and attitudes toward a particular group [5]. Some researchers suggest that implicit biases have little to no impact on behavior, but others argue they can change a person’s response to a particular situation, potentially leading to larger societal problems [4][6]. To encourage an open-minded and egalitarian society, it is important to understand the psychological and neurological basis of implicit biases and learn how to minimize possible behavioral effects.

About twenty years ago, Anthony Greenwald, a social psychologist at the University of Washington, described a method for assessing implicit biases that has since become a popular tool in social psychology research: the Implicit Association Test (IAT) [5]. The IAT measures an individual’s response time while associating concepts. For example, the race IAT asks subjects to quickly categorize pictures of African Americans and European Americans coupled with words with either positive or negative connotations. For instance, “flower” has a positive connotation and “weapon” has a negative connotation. Greenwald hypothesized that individuals should respond faster when they interpret two pictures to be closely related.   He also reasoned that discordant associations take longer to process, so participants should respond more slowly. For example, participants often take longer to associate a picture of a member of a different race with a positive word if they hold an implicit bias against members of that race [5]. Multiple versions of the IAT now exist to assess not only racial biases, but also religious, ethnic, gender, age, sexuality, disability, and weight biases [7]. They are available for free online and can be taken at home [7].

These tests often reveal automatic and unconscious preferences for one group over another, a finding that is concerning but unsurprising when considered within the context of human psychology [5]. Humans have a tendency to dichotomize along lines of “us” and “them" [8]. Individuals make automatic decisions regarding group membership, classifying some people as belonging to the same group as themselves (the “ingroup”) and other people as belonging to a different group (the “outgroup”) [9]. People make these subconscious classifications frequently to establish group membership, which is a major part of social identity and the development of self-esteem [10]. Individuals also tend to prefer members of the ingroup and can have more negative attitudes toward the outgroup [8].

Importantly, researchers have shown that ingroup favoritism can exist even when groups are designated arbitrarily [11]. Social psychologist Henri Tajfel was one of the first to demonstrate this principle. He asked a group of adolescent boys to estimate the number of dots in a cluster. The boys were then told that some people consistently overestimate the number of dots, and others underestimate. Then, when given a list of participants categorized only by whether they overestimated or underestimated, each boy was more likely to allocate money to boys who performed similarly to himself. This shows that group membership based on a minimal factor can induce an ingroup preference, even when there is no ideological explanation for favoring one group or disliking the other [11].

Additionally, past experiences and sociocultural influences substantially modulate attitudes. Consider, for example, the fact that when white participants take a race IAT, most exhibit a pro-white bias [10][12]. Counter to the expectations of standard ingroup-outgroup social dynamics, black participants are likely to exhibit no bias or even a pro-white bias [10][12]. One study found that young black adults who attended a predominantly black school for K-12 education tended to hold a pro-black bias, but those who did not tended to hold no bias [10]. This suggests that social structure and learning may play a role in implicit bias development. An idea known as system justification theory offers a similar but distinct explanation [13]. According to this theory, social groups within a sociopolitical system are influenced by a desire to maintain the existing condition of the system, no matter where the group falls on the social hierarchy. Thus, dominant groups are likely to maintain pro-ingroup attitudes that perpetuate their dominance, and non-dominant groups are likely to exhibit muted ingroup bias. The system itself is a result of a learned social structure [13].

While most research surrounding implicit biases falls in the domain of psychology and sociology, a subset of studies has sought to understand the neural mechanisms underlying their existence. Many have implicated the amygdala, an area of the brain involved in emotional learning and evaluation [14]. Multiple studies found increased activity in the amygdala when individuals saw a picture of a member of a racial outgroup as opposed to a member of their own race [9][14][15][16][17]. Most of these studies have analyzed the amygdala activity of white individuals looking at African American faces. There is a large body of literature that suggests the amygdala can signal stimuli as potential threats [18]. For example, patients with amygdala damage are more likely to trust a partner in a game after being betrayed because they are unable to identify the threat of untrustworthiness [18]. Increased amygdala activity after viewing a picture of a member of another race is therefore hypothesized to reflect an individual’s automatic interpretation of the face they see as a potential threat [9][14].

Interestingly, amygdala activation correlates with measures of implicit bias, but not with measures of explicit bias [14][15]. Individuals who exhibit greater amygdala activation when viewing the face of a racial outgroup member also tend to exhibit greater implicit biases measured by an IAT. This underscores the automaticity of the brain’s implicit emotional responses. On the other hand, differential amygdala activation to racial ingroup versus outgroup faces has no correlation with self-reported measures of explicit prejudice. Explicit racial prejudice is often measured with the Modern Racism Scale, which assesses the extent to which participants agree or disagree with racial statements, such as “Discrimination against blacks is no longer a problem in the United States’’ or ‘‘It is easy to understand the anger of black people in America" [15]. The scale is intended to measure attitudes regarding the current status of blacks in America as a proxy for explicit attitudes directly toward the group [15]. As mentioned above, responses do not correlate with amygdala activation. The brain may automatically respond differently to racial outgroup faces even in people who consciously feel that they are unprejudiced or choose to lead unprejudiced lifestyles, introducing the potential for subconsciously-influenced prejudiced behavior [14][15].

Studies of empathy may offer insight into the nature of such prejudiced behavioral effects. Differences in empathy responses to different groups may be attributable to implicit biases toward or against those groups. According to one study, when a participant viewed a picture of a face receiving a painful stimulus, activation of the anterior cingulate cortex (ACC) increased [19]. The ACC is an area of the brain involved in emotional empathy, so ACC activation is often used as a measure of empathy response. Importantly, ACC activation was greater for white participants when viewing a white face than when viewing a Chinese face. In the same study, ACC activation was greater in Chinese participants when viewing a Chinese face than a white face. This suggests that empathy was greater for members of a participant’s own race, which can influence social behaviors toward each group [19].

These behavioral effects may be subtle, but they can be a substantial barrier to achieving an egalitarian society. For instance, one study showed that recruiters of European background are more likely to invite a man with a Swedish name for an interview than a man with an Arab name, even when both are equally qualified [20]. This preference correlates with the degree of the recruiters’ implicit bias as measured by an IAT [20].

Notably, when individuals are pressured to make immediate decisions, the effects of implicit biases become even more pronounced. Many people who exhibit implicit biases deny explicit biases and try to act without prejudice [21]. However, when an individual is placed under pressure and forced to make a rapid evaluation, there may not be time for cognition and volition to take over. For example, a few studies have shown that white participants in a shooting simulation are more likely to shoot unarmed blacks than unarmed whites, especially those unarmed blacks with darker skin [22][23][24].

Current research has made some initial progress in modulating implicit biases and diminishing their effects on behavior, but there is much more to learn. Multiple studies suggest that implicit biases tend to develop very early in childhood [10][12][13]. A study in 2016 assessed not only the presence of implicit biases in children, but the strength with which they are held [25]. Researchers separated non-black children (including whites and Asians) into three random groups to take an IAT. Before the test, researchers read vignettes to the children, in which the children learned positive facts about four individuals, accompanied by a photograph of each individual. Children in different groups heard the same set of facts, but one group saw pictures of black individuals while the other saw pictures of white individuals. A third group, the control, heard vignettes about flowers and saw pictures of flowers. After this exposure, the children took a child-friendly IAT. Interestingly, younger children exhibited an implicit pro-white bias in all conditions, but older children were impacted by the vignettes. The older children exposed to positive black individuals held no implicit bias against blacks, whereas those who saw white individuals or flowers held an implicit bias against blacks. Incidentally, these findings suggest a developmental difference in the flexibility of implicit biases, which may be an important consideration for future research. However, the primary finding was that exposure to black exemplars can mitigate implicit bias in older children [25]. In general, other studies support these findings, with many showing that exposure to racial outgroup role models and interaction with members of racial outgroups can reduce implicit bias [26][27]. Unfortunately, another study found that the impact of exposure-based interventions is short-lived [28]. One hypothesis is that exposure to positive role models is outcompeted by consistent exposure to cultural influences that perpetuate the biases [28].

Reduction of implicit biases could be an important step toward neutralizing the current inequities between advantaged and disadvantaged groups. However, mechanisms for achieving long-term changes have yet to surface. As research continues, educational methods for mitigating biases may arise, but it is still up for debate whether such implicit bias interventions will actually alter behavior in meaningful ways [28][6]. With that said, research is likely to make strides toward understanding the developmental differences that characterize implicit biases and may even target these differences in developing solutions. In the meantime, understanding that implicit biases are defined by a learning component is the best way to combat them. Awareness of this principle may help eliminate the sociocultural patterns of inequities and the resulting stereotypes that promote bias against stigmatized groups. Moreover, while much of the research surrounding implicit biases seeks to address racial and ethnic disparities, it is important to understand that people can also hold implicit biases along many other ingroup-outgroup lines. These may include gender, sexuality, and disability, among other aspects of social identity. In all of these cases, in order to promote an equitable society, it is important to be mindful of implicit biases and their potential to negatively impact behavior.


  1. Humes, K. R., Jones, N. A., & Ramirez, R. R. (2011, March). Overview of Race and Hispanic Origin: 2010 – Census. Retrieved January 19, 2018, from
  2. Bloome, D. (2014). Racial Inequality Trends and the Intergenerational Persistence of Income and Family Structure.    American Sociological Review,    79    (6), 1196-1225. doi:10.1177/0003122414554947
  3. Bailey, Z. D., Krieger, N., Agénor, M., Graves, J., Linos, N., & Bassett, M. T. (2017). Structural racism and health inequities in the USA: evidence and interventions.    The Lancet,    389    (10077), 1453-1463. doi:10.1016/s0140-6736(17)30569-x
  4. Greenwald, A. G., Banaji, M. R., & Nosek, B. A. (2015). Statistically small effects of the Implicit Association Test can have societally large effects.    Journal of Personality and Social Psychology,108    (4), 553-561. doi:10.1037/pspa0000016
  5. Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. K. (1998). Measuring individual differences in implicit cognition: The implicit association test.    Journal of Personality and Social Psychology, 74    (6), 1464-1480. doi: 10.1037/0022-3514.74.6.1464
  6. Oswald, F. L., Mitchell, G., Blanton, H., Jaccard, J., & Tetlock, P. E. (2013). Predicting ethnic and racial discrimination: A meta-analysis of IAT criterion studies.    Journal of Personality and Social Psychology, 105    (2), 171-192. doi: 10.1037/a0032734
  7. Project Implicit. (2011). Retrieved January 19, 2018, from
  8. Amiot, C. E., & Bourhis, R. Y. (2003). Discrimination and the Positive-Negative Asymmetry Effect: Ideological and Normative Processes.    Personality and Social Psychology Bulletin,    29    (5), 597-608. doi:10.1177/0146167203029005005
  9. Hart, A. J., Whalen, P. J., Shin, L. M., Mcinerney, S. C., Fischer, H., & Rauch, S. L. (2000). Differential response in the human amygdala to racial outgroup vs ingroup face stimuli.    NeuroReport,    11    (11), 2351-2354. doi:10.1097/00001756-200008030-00004
  10. Gibson, B. L., Rochat, P., Tone, E. B., & Baron, A. S. (2017). Sources of implicit and explicit intergroup race bias among African-American children and young adults.    PLOS One,    12    (9). doi:10.1371/journal.pone.0183015
  11. Tajfel, H. (1970). Experiments in Intergroup Discrimination.    Scientific American,    223    (5), 96-102. doi:10.1038/scientificamerican1170-96
  12. Newheiser, A., & Olson, K. R. (2011). White and Black American children’s implicit intergroup bias.    Journal of Experimental Social Psychology,    48    (1), 264-270. doi:10.1016/j.jesp.2011.08.011
  13. Baron, A., & Banaji, M. (2009). Evidence of System Justification in Young Children.    Social and Personality Psychology Compass,    3    , 1-9. doi:10.1111/j.1751-9004.2009.00214.x
  14. Phelps, E. A., O’connor, K. J., Cunningham, W. A., Funayama, E. S., Gatenby, J. C., Gore, J. C., & Banaji, M. R. (2000). Performance on Indirect Measures of Race Evaluation Predicts Amygdala Activation.    Journal of Cognitive Neuroscience,    12    (5), 729-738. doi:10.1162/089892900562552
  15. Cunningham, W. A., Johnson, M. K., Raye, C. L., Gatenby, J. C., Gore, J. C., & Banaji, M. R. (2004). Separable neural components in the processing of black and white faces.    Psychological Science,    15    (12), 806-813. doi:10.1037/e633962013-151
  16. Ronquillo, J., Denson, T. F., Lickel, B., Lu, Z., Nandy, A., & Maddox, K. B. (2007). The effects of skin tone on race-related amygdala activity: an fMRI investigation.    Social Cognitive and Affective Neuroscience,    2    (1), 39-44. doi:10.1093/scan/nsl043
  17. Stanley, D. A., Sokol-Hessner, P., Fareri, D. S., Perino, M. T., Delgado, M. R., Banaji, M. R., & Phelps, E. A. (2012). Race and reputation: perceived racial group trustworthiness influences the neural correlates of trust decisions.    Philosophical Transactions of the Royal Society B: Biological Sciences,    367    (1589), 744-753. doi:10.1098/rstb.2011.0300
  18. Koscik, T. R., & Tranel, D. (2011). The human amygdala is necessary for developing and expressing normal interpersonal trust.    Neuropsychologia,    49    (4), 602-611. doi:10.1016/j.neuropsychologia.2010.09.023
  19. Xu, X., Zuo, X., Wang, X., & Han, S. (2009). Do You Feel My Pain? Racial Group Membership Modulates Empathic Neural Responses.    Journal of Neuroscience,    29    (26), 8525-8529. doi:10.1523/jneurosci.2418-09.2009
  20. Rooth, D. (2010). Automatic associations and discrimination in hiring: Real world evidence.    Labour Economics,    17    (3), 523-534. doi:10.1016/j.labeco.2009.04.005
  21. Cunningham, W. A., Nezlek, J. B., & Banaji, M. R. (2004). Implicit and Explicit Ethnocentrism: Revisiting the Ideologies of Prejudice.    Personality and Social Psychology Bulletin,    30    (10), 1332-1346. doi:10.1177/0146167204264654
  22. Kahn, K. B., & Davies, P. G. (2010). Differentially dangerous? Phenotypic racial stereotypicality increases implicit bias among ingroup and outgroup members.    Group Processes & Intergroup Relations,    14    (4), 569-580. doi:10.1177/1368430210374609
  23. Peruche, B. M., & Plant, E. A. (2006). The Correlates of Law Enforcement Officers Automatic and Controlled Race-Based Responses to Criminal Suspects.    Basic and Applied Social Psychology,28    (2), 193-199. doi:10.1207/s15324834basp2802_9
  24. Correll, J., Park, B., Judd, C. M., & Wittenbrink, B. (2002). The police officers dilemma: Using ethnicity to disambiguate potentially threatening individuals.    Journal of Personality and Social Psychology,    83    (6), 1314-1329. doi:10.1037/0022-3514.83.6.1314
  25. Gonzalez, A. M., Steele, J. R., & Baron, A. S. (2016). Reducing Children’s Implicit Racial Bias Through Exposure to Positive Out-Group Exemplars.    Child Development,    88    (1), 123-130. doi:10.1111/cdev.12582
  26. Columb, C., & Plant, E. A. (2011). Revisiting the Obama Effect: Exposure to Obama reduces implicit prejudice.    Journal of Experimental Social Psychology,    47    (2), 499-501. doi:10.1016/j.jesp.2010.11.012
  27. Lai, C. K., Marini, M., Lehr, S. A., Cerruti, C., Shin, J.-E. L., Joy-Gaba, J. A., . . . Nosek, B. A. (2014). Reducing implicit racial preferences: I. A comparative investigation of 17 interventions.    Journal of Experimental Psychology: General, 143    (4), 1765-1785. doi: 10.1037/a0036260
  28. Lai, C.K., Skinner, A.L., Cooley, E. ,Murrar, S., Brauer, M., Devos, T.,…Nosek, B.A. (2016). Reducing Implicit Racial Preferences: II. Intervention Effectiveness Across Time.    Journal of Experimental Psychology: General,    145    (8), 1001-1016. doi:10.1037/xge0000179