Implicit Racial Associations: Opening Up Questions for College Instructors

Over the next few weeks we present a series of blog posts exploring the role of implicit bias in teaching. The theme for these posts coincides with the National Underground Railroad Freedom Center’s exhibition Implicit Bias & How It Affects Our Everyday Thoughts and Behaviors now on exhibit at the UConn Homer Babbidge Library. 

Since the groundbreaking work of Rosenthal in the 1960s, it’s been known that instructors’ expectations of learners can affect their performance. It’s not some magical transference of belief that causes this phenomena, but rather the accumulation of simple behaviors on behalf of the instructor–waiting longer for the student to answer, giving more feedback, encouraging the learner when they are hesitant. Ideally, a teacher is able to hold high expectations and send see promise in every student. However, there is often an unseen force at work that shapes instructor expectations–implicit bias. Expectations are just one way that implicit bias manifests in the classroom.

Professor Thomas Craemer
Thomas Craemer is an Associate Professor in the online Graduate Program in Survey Research. His work has included using reaction time measures to tap people’s implicit racial attitudes and published a number of papers based on that research. Craemer also addressed the issue of racial divides in his research paper “Implicit Closeness to Blacks, Support for Affirmative Action, Slavery Reparations, and Vote Intentions for Barack Obama in the 2008 Elections,” which received the International Society of Political Psychology’s Roberta Sigel Award in 2010.

We begin our Implicit Bias series by looking more closely at the nature of implicit racial associations, presented here by Associate Professor of Public Policy Dr. Thomas Craemer. 

Implicit Racial Associations: Bad News and Good News

What are implicit associations? The term “implicit” refers to measurements of attitudes, not to the attitudes themselves. It implies that a reaction-time task has been employed to measure the attitude. An attitude measured at the implicit level may be conscious or non-conscious. The crucial point is that reaction-time measurements minimize a respondent’s conscious ability to control the response. Researchers have developed reaction time tasks to measure automatic associations at the implicit level and the most common of these procedures is called the Implicit Association Test (IAT). You can try it out yourself at Harvard University’s Project Implicit ( However, beware, if you are like me, you may be sorely disappointed in your own performance!

Before I share my disappointing IAT results, let me introduce myself to set the stage. I moved to this country from Germany 17 years ago because I was attracted to the greater degree of racial, ethnic, and cultural diversity in the United States. Fourteen of those years I lived in an interracial relationship residing in predominantly non-White neighborhoods like Harlem and later the South Bronx, New York, where I still live. My research focuses on implicit racial attitudes and pro-Black policies, including slavery reparations. In my spare time I sing in a Harlem gospel choir. When I took the Race IAT, I expected to score pro-Black. Instead the feedback I received stated: “Your data suggest a moderate automatic preference for White people compared to Black people.” The term preference rubbed me the wrong way. Having a preference, in my mind, implies something specific, for example what neighborhood you wish to live in and what company you seek, including romantic relationships. In contrast the term implicit association is more general. It could be due to shared culture, or represent implicit knowledge of bias rather than its endorsement.

Two very painful and embarrassing incidents convinced me that my implicit anti-Black association bias was real despite my pro-Black conscious convictions. The first example was on a sunny day in St. Mary’s Park in the South Bronx. I was tanning and minding my own business when a group of young Black males approached me in what I perceived to be an aggressive way. To defuse the situation I said: “Hi how are you guys doing?” And they responded in kind. Based on my accent they asked me where I was from and a long conversation ensued. After the guys left I asked myself why I had perceived them as “aggressive” when their approach had clearly been friendly. An example of anti-Black implicit bias – at least in this instance I did not act on it. This was different during the second example when I was riding an incredibly packed New York bus. The guy standing behind me was young, Black, with baseball cap askew and sagging pants. When I left the bus I reached for my back pocket and found my wallet missing. I immediately turned around and confronted the guy: “Did you take my wallet!?” The guy said “no.” I reached in my front pocket where I had put my wallet for safekeeping – it had slipped my mind. I apologized profusely to the guy who was very gracious and accepted my apology. This time I had exhibited racially discriminatory behavior towards a perfectly innocent fellow passenger! To this day my toe-nails curl at this embarrassing incident. When I introspect about the conditions under which my anti-Black implicit association bias manifests itself in racist behavior it is under stress or time pressure, when I do not have enough time to think. And these are precisely the conditions that the IAT simulates.

The bad news are that the race IAT tends to show that most respondents harbor a pro-White and anti-Black association bias – this is true of most White respondents (e.g., Greenwald et al., 1998), but also of many non-White respondents (e.g., Dasgupta et al., 2000) including African Americans (e.g., Ashburn-Nardo, Knowles, & Monteith, 2003). According to Project Implicit’s feedback page in its current form (viewed 1/26/2017), 70% of respondents who have visited the site have displayed the same pro-White and anti-Black implicit association bias as I did, while only 17% displayed no bias, and 12% a pro-Black bias). Further, this culturally shared anti-Black bias can be measured using other implicit measurement procedures, like subliminal racial priming (Craemer 2010). While respondents have to pay conscious attention to racial stimuli in the IAT, subliminal racial priming displays them only for a split second so respondents do not become aware of them. Yet the results are the same. In a study with 555 college students I ran in 2003 and 2004, for example, I found statistically significant pro-White and anti-Black subliminal priming biases among White students, among Black students, and among students of other backgrounds alike (data source: Craemer 2014).

But there are also good news: Not all implicit association measures show the pro-White and anti-Black association bias. I’ve been using a measure of implicit racial identification for many years that consistently shows pro-Black associations not only among Black respondents but also among some White respondents and respondents of other backgrounds (Craemer 2010, 2014). To deal with this complication, I am introducing a conceptual distinction, between evaluative associations and relational associations. Evaluative associations are good-bad assessments while relational associations are close-distant assessments. I find that the same individual respondent can have pro-Black relational associations while at the same time possessing a statistically significant anti-Black evaluative bias.

These results suggest that it is possible to have both anti-Black evaluative associations and pro-Black relational associations at the same time. Fortunately, the latter seem to matter more politically. I conclude optimistically that the implicit relational association measure may provide a direct psychological mechanism for pro-Black minority representation in a society based on majority decision making where the majority is non-Black and holds an ingrained anti-Black evaluative association bias.

So what does all this suggest for current and upcoming college educators? As a starting point, it propels us to examine our own biases. Becoming conscious of our biases will help us reflect on whether our actions are rooted in any implicit prejudices. It can also aid in recognizing bias in interactions between students. Are some students being left out of activities and discussions? Are their comments and ideas not given proper attention? Are students being tokenized? Knowledge of the common negative evaluative association gives us a sharper eye to look out for these problematic biases and their impact in the teaching and learning environment.



Four Ways Teachers Can Reduce Implicit Bias

Eight Actions to Reduce Racism in College Classrooms


Ashburn-Nardo, L., Knowles, M. L., & Monteith, M. J., 2003. Black Americans’ Implicit Racial Associations and their Implications for Intergroup Judgment. Social Cognition 21, 61–87.
Craemer, T., 2010. Possible Implicit Mechanisms of Minority Representation. Political Psychology 31(6), 797–829.
Craemer, T., 2014. Implicit Closeness to Blacks, Support for Affirmative Action, Slavery Reparations, and Vote Intentions for Barack Obama in the 2008 Elections. Basic and Applied Social Psychology 36, 413–424.
Dasgupta, N., McGee, D. E., Greenwald, A. G., & Banaji, M. R., 2000. Automatic Preference for White Americans: Eliminating the Familiarity Explanation. Journal of Experimental Social Psychology 36, 316–328.
Greenwald et al., 1998
Greenwald, A. G., McGhee, D. E., & Schwarz, J. L. K., 1998. Measuring Individual Differences in Implicit Cognition: The Implicit Association Test. Journal of Personality and Social Psychology 74, 1464–1480.
Rosenthal, R., & Jacobson, L. (1966). Teachers’ expectancies: Determinants of pupils’ IQ gains. Psychological reports, 19(1), 115-118.