Kate A. Ratliff’s research while affiliated with University of Florida and other places

The concept of implicit bias – the idea that the unconscious mind might hold and use negative evaluations of social groups that cannot be documented via explicit measures of prejudice – is a hot topic in the social and behavioral sciences. It has also become a part of popular culture, while interventions to reduce implicit bias have been introduced in police forces, educational settings, and workplaces. Yet researchers still have much to understand about this phenomenon. Bringing together a diverse range of scholars to represent a broad spectrum of views, this handbook documents the current state of knowledge and proposes directions for future research in the field of implicit bias measurement. It is essential reading for those who wish to alleviate bias, discrimination, and inter-group conflict, including academics in psychology, sociology, political science, and economics, as well as government agencies, non-governmental organizations, corporations, judges, lawyers, and activists.

This research tested whether institutional change impacts policy support and attitudes toward the social groups impacted by policy change. Study 1 demonstrated across a variety of topics that, when a hypothetical state legislature banned (vs. affirmed) a practice (e.g., allowing companies to implement mandatory anti-racism training), participants perceived less support for the policy and more negative attitudes toward the group impacted (e.g., Black Americans). Study 2, a longitudinal study, investigated the short- and long-term impact of real-world policy change—the U.S. Supreme Court’s Dobbs v. Jackson Women’s Health Organization ruling that gave states the right to restrict access to abortion. Although the ruling did not produce lasting change in personal support for abortion restriction, it did lead participants to perceive more support for traditional gender roles and to personally endorse traditional gender attitudes more strongly. These results demonstrate the power of institutional policies to influence individually held intergroup attitudes.

Among the general public and behavioral scientists alike, the Implicit Association Test (IAT) is the best known and most widely used tool for demonstrating implicit bias: the unintentional impact of social group information on behavior. More than forty million IATs have been completed at the Project Implicit research website. These public datasets are the most comprehensive documentation of IAT and self-reported bias scores in existence. In this essay, we describe the IAT procedure, summarize key findings using the IAT to document the pervasiveness and correlates of implicit bias, and discuss various ways to interpret IAT scores. We also highlight the most common uses of the IAT. Finally, we discuss unanswered questions and future directions for the IAT specifically, and implicit bias research more generally.

People who are more defensive about their feedback on the Race-Attitudes Implicit Association Test (IAT) are less willing to engage in anti-bias behaviors. Extending on this work, we statistically clarified defensiveness constructs to predict willingness to engage in anti-bias behaviors among people who received pro-White versus no-bias IAT feedback. We replicated the finding that U.S. Americans are generally defensive toward pro-White IAT feedback, and that more defensiveness predicts less willingness to engage in anti-bias behaviors. However, people who believed their pro-White IAT feedback was an inaccurate reflection of their “true attitudes” were more willing to engage in anti-bias behaviors compared with people who received no-bias IAT feedback. These results better illuminate the defensiveness construct suggesting that receiving self-threatening feedback about bias may motivate people’s willingness to engage in anti-bias behaviors in different ways depending on how people respond to that feedback.

Providing people with feedback about their intergroup biases is a central part of many diversity training and other bias‐education efforts. Although this practice may increase self‐awareness, people sometimes respond negatively to learning about their own biases. In the present review, we provide a framework for understanding when feedback about intergroup bias should lead to behavior change intentions, and when it can work against that goal. Specifically, we suggest that feedback about performance on measures of bias (e.g., the Implicit Association Test) will cause psychological discomfort to the extent that feedback about intergroup bias is: (1) discrepant from self‐reported attitudes, and (2) more personally or socially unacceptable than self‐reported attitudes. We then suggest two possible routes stemming from that psychological discomfort: If people accept personal responsibility for feedback, they will respond to psychological discomfort with compunction and direct efforts toward behavior and attitude change. By contrast, if people reject personal responsibility for feedback, they will respond defensively, derogating the feedback and trying to prove that the results are inaccurate. We use responses to feedback about implicit bias as a test case to demonstrate our model and discuss the current state of the literature on responding to IAT feedback. We also discuss interventions that can move people from defensiveness to compunction and open our metaphorical “file drawer” to discuss lessons learned.

The present research investigates whether benevolent and hostile sexist attitudes are differentially directed toward Black and White women by Black and White people. Participants (N = 2,775) reported on their sexist attitudes while thinking about Black women, White women, or women in general. Although Black participants reported higher levels of benevolent and hostile sexism overall, participant race and target race interacted to produce unique patterns of sexist attitudes. More specifically, Black perceivers thinking of White women reported higher levels of hostile sexism than those thinking of Black women. White perceivers reported similar amounts of hostile sexism while thinking of White and Black women. Benevolent sexism showed a different pattern, with both Black and White participants reporting higher levels of benevolent sexism toward Black than White women. The results also revealed similar levels of sexism reported while thinking of White women and while thinking of women in general, suggesting that sexism research that does not specifically address target race may reflect an understanding of sexist attitudes about White women that may not generalize to other racial groups.

Can people learn about implicit bias through an online course? We developed a brief (∼30 min) online educational program called Understanding Implicit Bias (UIB) consisting of four modules: (a) what is implicit bias? (b) the Implicit Association Test, (c) implicit bias and behavior, and (d) what can you do? In Experiment 1, we randomly assigned 6,729 college students across three separate samples to complete dependent measures before (control group) or after (intervention group) the UIB program. In Experiment 2, we randomly assigned 389 college students to complete the UIB program (intervention group) or two TED talks (control group) before dependent measures. Compared to control groups, the intervention groups had significantly higher objective knowledge about bias (ds = 0.39, 1.49) and subjective knowledge about bias (ds = 1.43, 2.61), awareness of bias (ds = 0.10, 0.54), and behavioral intentions to reduce bias (ds = 0.19, 0.84). These differences were again observed at a 2-week follow-up. These results suggest that brief online education about bias can affect knowledge and awareness of bias, as well as intentions to change behavior.

The present research investigates whether benevolent and hostile sexism are applied differentlyby Black and White U.S. Americans to Black and White women. Participants reported theirsexist attitudes while thinking about Black women, White women, or women in general.Although Black participants reported higher levels of benevolent and hostile sexism overall,participant race and target race interacted to produce unique effects on sexist attitudes. Morespecifically, Black perceivers thinking of White women reported higher levels of hostile sexismthan those thinking of Black women. White perceivers thinking of Black women reported higherlevels of hostile sexism than those thinking of White women. With regard to benevolent sexism,participants thinking of Black women reported higher levels of benevolent sexism than did thosethinking of White women. The results also suggested more similarity between sexism towardWhite women and sexism toward women in general, suggesting that our current understanding ofsexism better reflects an understanding of sexism directed toward White women rather thanwomen in general, suggesting the necessity for further research that considers the role of targetand perceiver race in understanding sexist attitudes.

In the current study we move away from bias-focused, White-centric research to examine relationships between gender, race/ethnicity, and weight-related attitudes, identity, and beliefs among Black, Black/White Biracial, East Asian, Hispanic/Latino, Native American, South Asian, and White U.S. Americans who self-identify as higher weight. The results showed that: (1) women identify as fat more than men do, (2) fat identity, operationalized as feelings of similarity to fat people (self-stereotyping) and importance of weight to one's sense of self (identity centrality) are relatively similar across races and ethnicities, and (3) fat identity and weight-related beliefs are related to positivity toward fat people across the racial/ethnic groups sampled in this study.