International Journal of Education and Social Science

The rapid integration of Artificial Intelligence (AI) into higher education offers substantial opportunities while simultaneously raising critical concerns related to ethics, safety, and trust. This study investigates how key dimensions of AI ethics named Human Rights, Autonomy, Bias, Fairness, Transparency, and Safety influence Trust in AI and, subsequently, university students’ Intention to Use AI. The proposed relationships are examined using Partial Least Squares Structural Equation Modeling (PLS-SEM). The measurement model is assessed in terms of internal consistency reliability, convergent validity, discriminant validity, and collinearity through Cronbach’s alpha, rho_A, rho_C, Average Variance Extracted (AVE), HTMT, the Fornell–Larcker criterion, and VIF. The findings highlight Safety as a particularly influential determinant of Trust in AI, while Trust in AI positively contributes to students’ intention to use AI technologies. At the same time, the measurement assessment reveals discriminant validity concerns between Transparency and Intention to Use AI, indicating substantial empirical overlap that warrants further investigation. The study contributes to the emerging literature by proposing a human-centered and ethics-oriented AI adoption framework, positioning trust as a critical mechanism linking students’ ethical perceptions of AI systems with their behavioral intention to adopt them in higher education.