PSYCHOLOGICAL DETERMINANTS OF TRUST IN AI

Abstract

The article presents a theoretical and psychological analysis of the phenomenon of trust in artificial intelligence (AI) as a complex integrative construct that combines cognitive, emotional, and ethical-normative components. The relevance of the study is substantiated in the context of the digital transformation of society, where human interaction with intelligent systems becomes not only a technical but also a psychological process that influences users’ emotional well-being, sense of control, and mental health. The purpose of the article is to theoretically generalize contemporary approaches to studying trust in the “human-AI” system and to construct a generalized model of its psychological determinants. The methodological basis comprises systemic-structural and interdisciplinary approaches integrating achievements of cognitive, social, engineering, and ethical psychology. The synthesis of recent studies made it possible to distinguish three groups of factors that determine the level of user trust in artificial intelligence: individual- psychological (trust propensity, self-efficacy, emotional stability, ethical sensitivity), technological (competence, fairness, transparency, benevolence, social presence), and sociocultural (normative and cultural values, institutional trust, ethical regulation). The proposed author’s model demonstrates that trust is formed as a result of the interaction of these levels and functions as a mechanism of psychological regulation in human-technology relations. It corresponds to the FAT approach and the motives-based trust concept, but emphasizes internal psychological processes – cognitive interpretation, emotional regulation, and value-based evaluation. The scientific novelty of the study lies in the synthetic integration of interdisciplinary approaches into a holistic psychological model of trust in AI.