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Last updated September 10, 2019.
Overview
Conscious experience tells a convincing story about what we like or dislike, but often this story is disconnected from how we act. A police officer may value racial equality, for example, but treat a Black citizen more harshly than a White citizen without a justifiable reason for doing so. This disconnect between thought and action can be captured in measures of implicit biases, which assess automatically activated associations within the mind. We study how to address implicit or hidden biases to reduce social inequalities.
Understanding Hidden Prejudice, Stereotypes, and Discrimination
To combat intergroup biases, one must know how they operate. Ongoing work is examining hidden instances of prejudice, stereotyping, and discrimination across a variety of domains. This work includes the study of caste prejudice in India, gender stereotypes among surgeons (Salles et al., 2019), social categorization of bisexual individuals, and mental representations of who a “racist” is.
Some recent work has been studying how hidden biases in political communication may perpetuate misinformation. One line of work looks at implicit associations about truth and falsity. We are finding evidence of “truthiness”: Implicit associations about events track real-world political events, but also what people want to be true. Another line of work looks at biases in the political information we choose to share with others.
Psychological Interventions to Reduce Implicit Bias
To understand the forces that are most influential for changing implicit associations, we must also learn which specific strategies are most effective. To accomplish this, we organized a research contest to test many interventions simultaneously (Lai et al., 2014). Nine of the eighteen interventions we tested were effective at reducing implicit racial prejudice immediately.
However, temporary malleability of implicit associations does not guarantee long-term change. We sought to see if effective interventions from the research contest were effective in the long-term (Lai et al., 2016). We tested the nine successful interventions from the research contest again, and found that none continued to have an effect after a day. In ongoing research, we are examining whether new approaches (e.g., more intensive interventions, targeting different mechanisms) will reduce implicit bias in the long-term.
We have also recently found that changes in implicit bias do not necessarily translate to behavioral change In a meta-analysis with 494 experiments (Forscher*, Lai*, et al., 2019). The explanation for this finding is not yet clear. It may be due to measurement issues, research design issues, and/or a lack of direct influence by implicit biases themselves. Ongoing work is disentangling these various explanations.
Behaviorally-Focused Interventions to Reduce Discrimination
Reducing implicit bias will not effectively reduce discrimination in isolation. Effective approaches will require a focus on changing the behaviors that are most closely linked to discrimination on-the-ground.
One line of work has focused on education about implicit bias and diversity training, with a focus on law enforcement. In partnership with the Anti-Defamation League, we are training police officers on the science of hidden biases and educating them on strategies to mitigate their influence. Ongoing work is assessing the long-term impact of these trainings on officers’ beliefs and behavior.
Another line of work has examined changes in the ‘choice architecture’ of how people make decisions about others. One recent paper has examined how interventions to reduce discrimination by targeting randomness or noise in decision-making can be as effective as targeting hidden preferences (Axt & Lai, 2019).
* Co-lead-authors.
Diversity Science Lab 