Explainable AI and Algorithm Transparency on Employee Acceptance: The Mediating Role of Trust

Opis

Abstract— The rapid spread of artificial intelligence (AI) in companies has raised critical challenges regarding employee acceptance, particularly concerning trust and system understanding. This study investigates the impact of explainable AI (XAI) and algorithm transparency on employee acceptance, with trust acting as a mediating variable. Based on a user-centered AI approach, this study explores how different dimensions of AI design influence user perception and technology acceptance in the workplace. A quantitative approach was chosen, based on survey data from 200 employees with experience using AI systems. The data were analyzed using partial least squares structural equation modeling (SEM-PLS) to examine direct and indirect relationships between the variables. The results show that algorithm transparency has the strongest impact, significantly influencing both employee trust and acceptance. Furthermore, a significant indirect effect via trust is also observed. Trust also has a positive and significant impact on employee acceptance, thus confirming its role as a key psychological mechanism in AI adoption. In contrast, explainable AI shows a different pattern: It…

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