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Human perceivers continually react to the social world implicitly —that is, spontaneously and rapidly. Earlier research suggested that implicit impressions of other people are slower to change than self-reported impressions in the face of contradictory evidence, often leaving them miscalibrated from what one learns to be true. Recent work, however, has identified conditions under which implicit impressions can be rapidly updated. Here, we review three lines of work showing that implicit impressions are responsive to information that is highly diagnostic, believable, or reframes earlier experience. These findings complement ongoing research on mechanisms of changing implicit impressions in a wider variety of groups, from real people to robots, and provide support for theoretical frameworks that embrace greater unity in the factors that can impact implicit and explicit social cognition.

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Explicit evaluations of racial out-groups often involve conflict between opposing evaluative tendencies. Yet this type of conflict is difficult to capture with standard measures of evaluative processing, which either ignore explicit evaluation or capture only the aspects of explicit evaluation that are consciously accessible and freely reported. A new tool may fill this gap in our ability to measure conflict in racial evaluation. This tool, called the mouse-tracking measure of racial bias (Race-MT), is designed to capture conflict in explicit evaluations of racial groups, even if that conflict is neither consciously accessible nor freely reported. We vetted the Race-MT by exploring whether it predicts discriminatory behavior. Across five studies (four preregistered, N = 1,492), we used the Race-MT to measure conflict in people’s positive, explicit evaluations of racial out-groups versus in-groups. These measures predicted discriminatory behavior in a noisy, naturalistic setting, suggesting that the Race-MT provides theoretically meaningful and predicatively useful insights into racial evaluation.

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Recent work has shown that people can update their implicit evaluations based on facial trustworthiness. However, do these updated implicit evaluations map onto subsequent decisions? We examined whether implicit evaluations based on faces but updated in light of new behavioral evidence uniquely predict responses in the trust game. Across six studies ( N = 2,059), we measured participants’ initial implicit evaluations of a target based on the target’s face and then their updated implicit evaluations based on newly learned behavioral evidence. We then tested whether these updated implicit evaluations uniquely predicted (i.e., beyond explicit evaluations) responses in a hypothetical trust game. Although participants consistently based their initial evaluations on the face and updated their evaluations after learning new diagnostic information, their updated implicit evaluations did not uniquely predict their responses in the trust game. We discuss theoretical considerations in this article.