Jordan Axt’s research while affiliated with McGill University and other places

A great deal of research in dual process models has been devoted to highlighting differences in the structure and function of the implicit and explicit attitude constructs. However, the two forms of attitudes can also demonstrate important shared properties, and prior work suggests that one similarity may be in factors that determine measurement reliability. To better explore this issue, Study 1 analyzed the test-retest reliability in measures of both implicit and explicit attitudes within a single study session across 75 topics (N > 35,000). Explicit attitudes had greater test-retest reliability than implicit attitudes, but each showed considerable heterogeneity across topics, even when measured within a single study session. Analyses also included several candidate moderator variables, such as attitude certainty or familiarity. While results were not identical, the moderators associated with greater test-retest reliability for implicit and explicit attitudes exhibited more similarities than differences. Specifically, attitudes experienced as more distinctive, more relevant to one’s self-concept, more certain, and more accessible had higher test-retest reliability for both forms of evaluation. Variation in short-term reliability for implicit and explicit attitudes was replicated in Study 2, and Study 3 revealed that topics low in short-term reliability were also lower in a longitudinal sample that completed measures separated by several weeks. These results advance our understanding of each attitude construct, and are consistent with a more dynamic relationship between an attitude and its measure, as even attitudes measured with high levels of conscious control could show remarkable short-term instability when assessed only minutes apart.

Discrimination in the evaluation of others is a key cause of social inequality around the world. However, relatively little is known about psychological interventions that can be used to prevent biased evaluations. The limited evidence that exists on these strategies is spread across many methods and populations, making it difficult to generate reliable best practices that can be effective across contexts. In the present work, we held a research contest to solicit interventions with the goal of reducing discrimination based on physical attractiveness using a hypothetical admissions task. Thirty interventions were tested across four rounds of data collection (total N > 20,000). Using a Signal Detection Theory approach to evaluate interventions, we identified two interventions that reduced discrimination by lessening both decision noise and decision bias, while two other interventions reduced overall discrimination by only lessening noise or bias. The most effective interventions largely provided concrete strategies that directed participants’ attention towards decision-relevant criteria and away from socially biasing information, though the fact that very similar interventions produced differing effects on discrimination suggests certain key characteristics that are needed for manipulations to reliably impact judgment. The effects of these four interventions on decision bias, noise, or both also replicated in a different discrimination domain, political affiliation, and generalized to populations with self-reported hiring experience. Results of the contest for decreasing attractiveness-based favoritism suggest that identifying effective routes for changing discriminatory behavior is a challenge, and that greater investment is needed to develop impactful, flexible, and scalable strategies for reducing discrimination.

A great deal of research in dual-process models has been devoted to highlighting differences in the structure and function of the implicit and explicit attitude constructs. However, the two forms of attitudes can also demonstrate important shared properties, and prior work suggests that one similarity may be in factors that determine measurement reliability. To better explore this issue, Study 1 analyzed the test–retest reliability in measures of both implicit and explicit attitudes within a single study session across 75 topics (N > 35,000). Explicit attitudes had greater test–retest reliability than implicit attitudes, but each showed considerable heterogeneity across topics even when measured within a single study session. Analyses also included several candidate moderator variables, such as attitude certainty or familiarity. While results were not identical, the moderators associated with greater test–retest reliability for implicit and explicit attitudes exhibited more similarities than differences. Specifically, attitudes experienced as more distinctive, more relevant to one’s self-concept, more certain, and more accessible had higher test–retest reliability for both forms of evaluation. Variation in short-term reliability for implicit and explicit attitudes was replicated in Study 2, and Study 3 revealed that topics low in short-term reliability were also lower in a longitudinal sample that completed attitude measures separated by several weeks. These results advance our understanding of each attitude construct and are consistent with a more dynamic relationship between an attitude and its measure, as even attitudes measured with high levels of conscious control could show remarkable short-term instability when assessed only minutes apart.

Discrimination in the evaluation of others is a key cause of social inequality around the world. However, relatively little is known about psychological interventions that can be used to prevent biased evaluations. The limited evidence that exists on these strategies is spread across many methods and populations, making it difficult to generate reliable best practices that can be effective across contexts. In the present work, we held a research contest to solicit interventions with the goal of reducing discrimination based on physical attractiveness using a hypothetical admissions task. Thirty interventions were tested across four rounds of data collection (total N > 20,000). Using a signal detection theory approach to evaluate interventions, we identified two interventions that reduced discrimination by lessening both decision noise and decision bias, while two other interventions reduced overall discrimination by only lessening noise or bias. The most effective interventions largely provided concrete strategies that directed participants’ attention toward decision-relevant criteria and away from socially biasing information, though the fact that very similar interventions produced differing effects on discrimination suggests certain key characteristics that are needed for manipulations to reliably impact judgment. The effects of these four interventions on decision bias, noise, or both also replicated in a different discrimination domain, political affiliation, and generalized to populations with self-reported hiring experience. Results of the contest for decreasing attractiveness-based favoritism suggest that identifying effective routes for changing discriminatory behavior is a challenge and that greater investment is needed to develop impactful, flexible, and scalable strategies for reducing discrimination.

Understanding and reducing intergroup discrimination is at the forefront of psychological research. However, efforts to find flexible, scalable, and durable interventions to reduce discrimination have produced only mixed results. In this review, we highlight one potential avenue for developing new strategies for addressing discrimination: adapting prior research on debiasing—the process of lessening bias in judgment errors (e.g., motivated reasoning, overconfidence, and the anchoring heuristic). We first introduce a taxonomy for understanding intervention strategies that are common in the debiasing literature, then highlight existing approaches that have already proven successful for decreasing intergroup discrimination. Finally, we draw attention to promising debiasing interventions that have not yet been applied to the context of discrimination. A greater understanding of prior efforts to mitigate judgment biases more generally can expand efforts to reduce discrimination. Public Abstract Scientists studying intergroup biases are often concerned with lessening discrimination (unequal treatment of one social group versus another), but many interventions for reducing such biased behavior have weak or limited evidence. In this review article, we argue one productive avenue for reducing discrimination comes from adapting interventions in a separate field—judgment and decision-making—that has historically studied “debiasing”: the ways people can lessen the unwanted influence of irrelevant information on decision-making. While debiasing research shares several commonalities with research on reducing intergroup discrimination, many debiasing interventions have relied on methods that differ from those deployed in the intergroup bias literature. We review several instances where debiasing principles have been successfully applied toward reducing intergroup biases in behavior and introduce other debiasing techniques that may be well-suited for future efforts in lessening discrimination.

Understanding and reducing intergroup discrimination is at the forefront of psychological research. However, efforts to find flexible, scalable, and durable interventions to reduce discrimination have produced only mixed results. In this review, we highlight one potential avenue for developing new strategies for addressing discrimination: adapting prior research on debiasing—the process of lessening bias in judgment errors (e.g., motivated reasoning, overconfidence, the anchoring heuristic). We first introduce a taxonomy for understanding intervention strategies that are common in the debiasing literature, then highlight existing approaches that have already proven successful for decreasing intergroup discrimination. Finally, we draw attention to promising debiasing interventions that have not yet been applied to the context of discrimination. A greater understanding of prior efforts to mitigate judgment biases more generally can expand efforts to reduce discrimination.

Using a newly developed measure of implicit transgender attitudes, we investigate the association between state-level antitransgender policies and individual-level attitudes about transgender people among residents. In a large sample of U.S. participants ( N = 211,133), we find that individuals living in states with more discriminatory policies against transgender people (e.g., not allowing changes to one’s gender identity on official identity papers) exhibited more negative implicit and explicit transgender attitudes. This pattern held after controlling for participant race and gender, as well as when looking only at cisgender participants. These findings extend prior work concerning how intergroup biases relate to regional characteristics such as legislation and do so in a novel and consequential context. This research also informs ongoing work concerning the role of policy-making and social norms on the development and expression of intergroup prejudice.