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Federal and State Court Cooperation: What Is Bias and How Is It Measured?

There are multiple forms of bias that federal-state programs can address. This page defines explicit and implicit bias and examines how psychologists measure each type.

What Is Explicit Bias?

Explicit biases reflect attitudes or beliefs expressed at a conscious level of awareness. Decades of psychological research support a connection between explicit bias and behavior. Explicit attitudes can lead to stereotyping that affects decision-making processes and can lead to prejudicial behavior.

Explicit bias is often considered controllable. Educational programs often encourage people to identify their own biases and take steps to reduce them. Researchers often use self-report measures to identify explicit bias. For example, a self-report measure might ask people to rate the extent to which they agree or disagree with statements such as “Whites are more trustworthy than Blacks” or “it is likely that Black people will bring violence to neighborhoods if they move in.” Yet, these types of measures face limitations. Such overt questions may make people reluctant to answer in a prejudicial manner, even if they possess prejudicial beliefs, since research finds that people want to present themselves in a positive manner. Despite the limitations with self-reporting measures, explicit bias exists and is a pressing problem that warrants continued education and research.

What Is Implicit Bias?

Implicit bias results from nonconscious cognitive processes that may be automatically activated. Implicit bias literature examines the implicit stereotypes and attitudes that people may hold about groups or individuals. Some researchers prefer to use the term implicit preferences (instead of implicit bias) since this research is more focused on attitudes (preferences) than behaviors (bias). In fact, prominent researchers from the Project Implicit website have noted that, “The link between implicit bias and behavior is fairly small on average but can vary quite greatly.”

Because people are generally unaware of any implicit biases they hold, researchers cannot rely on overt survey-like measures to detect them. Instead, measures including the Implicit Association Test (IAT) have gained prominence. The IAT relies on psychological research showing that when people are presented with two opposing categories they react more slowly than when they are presented with two categories in agreement. For example, for the IAT examining racial associations, participants are provided with photos of people they must classify into racial categories (African American or European American) and words they must classify into evaluative terms (good or bad). As the IAT continues, the racial categories and evaluative terms are combined. Put simply, the logic behind the IAT is that people with a stronger, negative implicit associations toward African Americans will respond faster when a negative word is paired with a photo of an African American than when paired with a photo of a European American. There are many different types of IAT tests available, which allow for an examination of a variety of potential associations.

Another research paradigm, the police officer’s dilemma, finds that when presented with an image of a potential suspect who is either African American or European American and either armed with a gun or not, participants role-playing as police officers react more quickly and “shoot” suspects who are armed and African American.

Importantly, though the police officer’s dilemma involves concrete actions, neither that experiment nor the IAT offer definitive proof that implicit preferences correspond with biased behaviors in the real world. Instead, each experiment tests the strength of associations between groups (e.g., African Americans) and evaluations (e.g., good, bad, threatening, unthreatening) or stereotypes (e.g., untrustworthy, criminal) in a research setting. Thus, while these experiments offer an innovative look into implicit preferences, additional research is needed to examine how these preferences affect real world behaviors.

For more information on empirical evidence regarding the effectiveness of implicit bias programs, see

 

For more information on these topics, or to share relevant research findings, contact Jason A. Cantone at fedstate@fjc.gov