Abstract:
Artificial Intelligence (AI) is increasingly adopted in higher education to enhance teaching, learning, and administrative processes. While AI-driven systems offer significant potential benefits, their adoption in educational contexts raises critical ethical concerns that influence user trust and acceptance. Issues related to data privacy, fairness, transparency, accountability, and system reliability have emerged as key barriers to the responsible use of AI, particularly in developing-country higher education systems where institutional governance and ethical readiness remain limited. Existing technology acceptance models often regard AI as a neutral tool and fail to adequately address how ethical considerations influence behavioural intentions and actual usage. This paper introduces a conceptual framework for understanding ethical AI acceptance in higher education by combining ethical principles, trust, and the Theory of Planned Behaviour (TPB). The framework conceptualises four ethical principles: Privacy and Security, Fairness and Non-Discrimination, Transparency and Accountability, and Technical Integrity and Robustness as antecedents that influence trust in AI systems. Trust is posited as a central mediating mechanism influencing users’ behavioural intention and subsequent AI use. This study extends the Theory of Planned Behaviour (TPB) by incorporating ethical principles into AI decision-making. It shows that adopting AI in higher education is influenced by social values and ethics. The proposed framework offers theoretical insights into the role of ethics and trust in technology acceptance and provides practical guidance for universities and policymakers seeking to implement AI responsibly. Future research is encouraged to empirically validate the framework across diverse institutional and cultural contexts to support ethical and socially cohesive digital transformation in higher education.
