Date of Conferral

6-3-2025

Date of Award

June 2025

Degree

Ph.D.

School

Psychology

Advisor

Hedy Dexter

Abstract

The rapid integration of artificial intelligence (AI) into essential sectors, including healthcare, customer services, and defense, has underscored the importance of user trust in AI systems. Psychological traits such as locus of control (the extent to which individuals attribute outcomes to internal or external factors) and self-efficacy (individuals’ confidence in their ability) have been identified as significant factors influencing trust in these automated systems. Previous studies have independently linked these psychological traits to trust in technology; however, there has been limited exploration of potential moderating effects of locus of control on the relationship between digital technology self-efficacy and trust in AI. Grounded in Bandura’s self-efficacy theory and Rotter’s locus of control framework, this quantitative study examined the extent to which locus of control moderated the relationship between digital technology self-efficacy and trust in AI among English-speaking adults, 22 to 55, living in the United States. Using a cross-sectional correlational design, data were collected via Amazon’s Mechanical Turk from 125 participants. A moderated multiple regression analysis revealed digital technology self-efficacy, locus of control, and interactions did not significantly predict trust in AI. These findings indicated locus of control and self-efficacy may not significantly influence trust in AI as previously expected, highlighting the need to explore additional psychological or contextual factors affecting user attitudes. By encouraging continued investigation, these findings build a foundation for enhancing user confidence and supporting equitable AI adoption, thereby contributing to positive social change.

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