Paper Type

Complete

Abstract

As artificial intelligence increasingly structures digital decision environments, its effects extend beyond efficiency to users’ psychosocial well-being, including autonomy, cognitive strain, and affective responses. However, existing research largely assumes standardized user behavior, overlooking individual-level psychological variability. This exploratory study introduces a psychological perspective by examining how Jungian cognitive–affective characteristics relate to emotional and behavioral responses in AI-mediated decision-making among Generation Z. Based on a quantitative study (N = 140), the findings indicate that psychological characteristics are associated with variation in decision routines and emotional activation, particularly across decision stages. Extraversion is linked to greater engagement in information search, whereas introversion is associated with higher automation-related anxiety. These results suggest that AI systems function as psychologically contingent environments and highlight the importance of incorporating individual differences into the design of adaptive, human-centered AI systems.

Paper Number

1312

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Aug 15th, 12:00 AM

Human–AI Interaction and Digital Well-Being: The Role of Psychological Type in AI-Mediated Decision Processes

As artificial intelligence increasingly structures digital decision environments, its effects extend beyond efficiency to users’ psychosocial well-being, including autonomy, cognitive strain, and affective responses. However, existing research largely assumes standardized user behavior, overlooking individual-level psychological variability. This exploratory study introduces a psychological perspective by examining how Jungian cognitive–affective characteristics relate to emotional and behavioral responses in AI-mediated decision-making among Generation Z. Based on a quantitative study (N = 140), the findings indicate that psychological characteristics are associated with variation in decision routines and emotional activation, particularly across decision stages. Extraversion is linked to greater engagement in information search, whereas introversion is associated with higher automation-related anxiety. These results suggest that AI systems function as psychologically contingent environments and highlight the importance of incorporating individual differences into the design of adaptive, human-centered AI systems.

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