In this article, we describe four theoretical and methodological problems that have impeded implicit attitude research and the popular understanding of its findings. The problems all revolve around assumptions made about the relationships among measures (indirect vs. versus direct), constructs (implicit vs. explicit attitudes), cognitive processes (e.g., associative vs. propositional), and features of processing (automatic vs. controlled). These assumptions have confused our understandings of exactly what we are measuring, the processes that produce implicit evaluations, the meaning of differences in implicit evaluations across people and contexts, the meaning of changes in implicit evaluations in response to intervention, and how implicit evaluations predict behavior. We describe formal modeling as one means to address these problems, and provide illustrative examples. Clarifying these issues has important implications for our understanding of who has particular implicit evaluations and why, when those evaluations are likely to be particularly problematic, how we might best try to change them, and what interventions are best suited to minimize the effects of implicit evaluations on behavior.

Racial stereotypes are commonly activated by informational cues that are detectable in people's faces. Here, we used a sequential priming task to examine whether and how the salience of emotion (angry/scowling vs. happy/smiling expressions) or apparent race (Black vs. White) information in male face primes shapes racially biased weapon identification (gun vs. tool) decisions. In two experiments (N_total = 546) using two different manipulations of facial information salience, racial bias in weapon identification was weaker when the salience of emotion expression versus race was heightened. Using diffusion decision modeling, we tested competing accounts of the cognitive mechanism by which the salience of facial information moderates this behavioral effect. Consistent support emerged for an initial bias account, whereby the decision process began closer to the "gun" response upon seeing faces of Black versus White men, and this racially biased shift in the starting position was weaker when emotion versus race information was salient. We discuss these results vis-à-vis prior empirical and theoretical work on how facial information salience moderates racial bias in decision-making.

Forming impressions of others is a fundamental aspect of social life. These impressions necessitate the integration of many and varied sources of information about other people, including social group memberships, apparent personality traits, inferences from observed behaviors, and so forth. However, methodological limitations have hampered progress in understanding this integration process. In particular, extant approaches have been unable to measure the independent contributions of multiple features to a given impression. In this article, after describing these limitations and their constraints on theory testing and development, we present a multinomial processing tree model as a computational solution to the problem. Specifically, the model distinguishes the contributions of multiple cues to social judgment. We describe an empirical demonstration of how applying the model can resolve long-standing debates among person perception researchers. Finally, we survey a variety of questions to which this approach can be profitably applied. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

We argue that the dual-system approach and, particularly, the default-interventionist framework favored by De Neys unnecessarily constrains process models, limiting their range of application. In turn, the accommodations De Neys makes for these constraints raise questions of parsimony and falsifiability. We conclude that the extent to which processes possess features of system 1 versus system 2 must be tested empirically.

People sometimes prefer groups to which they do not belong (outgroups) over their own groups (ingroups). Many long-standing theoretical perspectives assume that this outgroup favorability bias primarily reflects negative ingroup evaluations rather than positive outgroup evaluations. To examine the contributions of negative ingroup versus positive outgroup evaluations to outgroup bias, we examined participants' data (total n > 879,000) from Implicit Association Tests [A. G. Greenwald, D. E. McGhee, J. L. K. Schwartz, J. Pers. Soc. Psychol. 74, 1464-1480 (1998)] measuring intergroup attitudes across four social domains in exploratory and preregistered confirmatory analyses. Process modeling [F. R. Conrey, J. W. Sherman, B. Gawronski, K. Hugenberg, C. J. Groom, J. Pers. Soc. Psychol. 89, 469-487 (2005)] was applied to the responses of participants who demonstrated implicit outgroup bias to separately estimate the contributions of negative ingroup and positive outgroup evaluations. The outgroup biases of lower-status group members (i.e., Asian, Black, gay and lesbian, and older people) consistently reflected greater contributions of positive outgroup evaluations than negative ingroup evaluations. In contrast, the outgroup biases of higher-status group members (i.e., White, straight, and younger people) reflected a more varied pattern of evaluations. We replicated this pattern of results using explicitly measured intergroup evaluations. Taking these data together, the present research demonstrates a positive-negative asymmetry effect of outgroup bias, primarily among members of lower-status groups.

Extending evidence for the rapid revision of mental representations of what other people are like, we explored whether people also rapidly revise their representations of what others look like. After learning to ascribe positive or negative behavioral information to a target person and generating a visualization of their face in a reverse-correlation task, participants learned new information that was (a) counter-attitudinal and diagnostic about the person's character or (b) neutral and non-diagnostic, and then they generated a second visualization. Ratings of these visualizations in separate samples of participants consistently revealed revision effects: Time 2 visualizations assimilated to the counter-attitudinal information. Weaker revision effects also emerged after learning neutral information, suggesting that the evaluative extremity of visualizations may dilute when encountering any additional information. These findings indicate that representations of others' appearance may change upon learning more about them, particularly when this new information is counter-attitudinal and diagnostic.