From AI Literacy to Digital Trust: A Human-Centred Framework for Ethical, Privacy-Aware and Equitable AI Adoption in Higher Education

The rapid integration of Artificial Intelligence (AI) and Generative AI into higher education is transforming teaching, learning, assessment, research, and information services. However, effective AI adoption requires more than technical proficiency; it demands AI literacy, ethical awareness, privacy protection, transparency, accountability, and digital trust. This study proposes a human-centred framework that connects AI literacy with responsible AI adoption in higher education. Drawing on recent research concerning AI literacy, ethical AI pedagogy, algorithmic fairness, data protection, governance, and students’ ethical judgment, the study examines how technological competencies and ethical reasoning can jointly influence trustworthy AI use. Particular attention is given to privacy risks, algorithmic bias, explainability, academic integrity, human oversight, and inequalities in access to AI-enabled educational resources. The proposed framework positions students, educators, institutions, and information professionals as active stakeholders in establishing responsible AI ecosystems. It further emphasizes that AI literacy should evolve from understanding AI tools toward the critical evaluation of AI-generated information, ethical decision-making, and responsible data practices. The framework can support higher education institutions in developing AI policies, curricula, training programmes, and governance mechanisms that strengthen digital trust while promoting innovation and educational equity. The study provides a foundation for future empirical research examining the relationship between AI literacy, ethical competence, privacy awareness, and trustworthy AI adoption.