Person Perception

Central to our research is the idea of stereotypes acting as predictive guides, shaping our expectations and interactions with individuals and groups.

Indeed, our findings indicate that the commonly observed facilitation of task performance by stereotypes is underpinned by an expectancy bias, suggesting that stereotypes are more than just categorizations — they are predictions. Additionally, our research uncovers that information contradicting stereotypes (stereotype-inconsistent) can sometimes be processed more efficiently. This adds a fascinating layer of complexity to our understanding of person perception.

Additionally, we delve into how group-related beliefs impact the acquisition of person knowledge, a less-explored area in the field of social cognition. Our findings suggest that gender stereotypes can significantly impact instrumental learning, influencing our expectancy-based preferences and learning rates.

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To unravel these complex cognitive mechanisms, we use an array of research methods, including probabilistic selection tasks and computational modeling techniques like the Reinforcement Learning Drift Diffusion Model.

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As we further explore the role of stereotypes as predictive tools in person perception, we aim to contribute valuable insights to various fields, from improving interpersonal communication to designing more empathetic artificial intelligence systems. Join us on this journey as we delve deeper into the cognitive underpinnings of how we perceive others and the profound impacts this process has on our social world."