Individualized Models of Social Judgments and Context-Dependent Representations

How individuals view the world is critical to understanding human behavior. Yet, almost all research within perception has drawn inferences from group-level behavior, with little work focused on understanding how the individual perceives their world. However, for complex judgments (e.g., trustworthiness), most of the meaningful variance is due to factors specific to the individual. Here we showcase a data-driven reverse correlation method for visualizing any perceptually-derived stereotype at the individual level. We show that our method 1) produces photorealistic and reliable results related to a broad range of judgments, 2) produces valid, psychologically-aligned representations of what individuals are imagining “in their mind’s eye”, and 3) is capable of capturing visual representations sensitive enough to examine context-dependent categories (e.g., a trustworthy individual to babysit your children vs. a trustworthy individual to fix your car). Across all studies, we highlight the theoretical implications and utility of developing idiosyncratic models of visual perception.