Albohn Daniel N, Uddenberg Stefan, Todorov Alexander
Booth School of Business, University of Chicago, Chicago, IL, USA.
Sci Rep. 2025 Feb 4;15(1):4208. doi: 10.1038/s41598-025-86056-1.
How individuals view the world is critical to understanding human behavior. Yet, almost all research within perception and judgment 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. to fix your car). Across all studies, we highlight the theoretical implications and utility of developing idiosyncratic models of visual perception.
个体如何看待世界对于理解人类行为至关重要。然而，几乎所有关于感知和判断的研究都是从群体层面的行为中得出推论，很少有工作专注于理解个体如何感知他们的世界。然而，对于复杂的判断（例如可信度），大部分有意义的差异是由个体特有的因素造成的。在这里，我们展示了一种数据驱动的反向相关方法，用于在个体层面可视化任何从感知中衍生出的刻板印象。我们表明，我们的方法（1）产生与广泛判断相关的逼真且可靠的结果，（2）产生个体在“脑海中想象”的有效、心理上一致的表征，并且（3）能够捕捉足够敏感的视觉表征以检查依赖于上下文的类别（例如，一个值得信赖的人来照顾你的孩子与修理你的汽车）。在所有研究中，我们强调了开发个性化视觉感知模型的理论意义和实用性。
