Accumulated findings from studies in which implicit-bias measures correlate with
discriminatory judgment and behavior have led many social scientists to conclude that …

Algorithm aversion is an important and persistent issue that prevents harvesting the benefits
of advancements in artificial intelligence. The literature thus far has provided explanations …

This article provides a guide for rigorous, theory-driven measurement approaches,
proposing best practices for the scientific study of systemic racism in health research. We …

Importance Racial implicit bias can contribute to health disparities through its negative
influence on physician communication with Black patients. Interventions for physicians to …

In the past two decades, a variety of cognitive training interventions have been developed to
help people overcome their addictive behaviors. Conceptually, it is important to distinguish …

We introduce the test difficulty concept from classical test theory to tackle the issue of low
predictive power of implicit association tests (IATs). Following classical test theory, we argue …

Beyond conscious beliefs and goals, automatic cog-nitive processes shape our social
encounters, and interactions with complex machines like social robots are no exception …

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 …

Abstract The Implicit Association Test (IAT), like many behavioral measures, seeks to
quantify meaningful individual differences in cognitive processes that are difficult to assess …

Using a newly developed measure of implicit transgender attitudes, we investigate the
association between state-level antitransgender policies and individual-level attitudes about …