Artificial Intelligence in Higher Education: The Role of Fairness, Transparency, and Accountability in Student Acceptance

Abstract

This study examined the influence of Fairness, Transparency, and Accountability [FTA] on student acceptance of Artificial Intelligence [AI] in higher education institutions in Khyber Pakhtunkhwa, Pakistan. Grounded on an extended Technology Acceptance Model, data were collected from 240 undergraduate students from six universities using a structured 5-point likert scale questionnaire. Descriptive analysis and Pearson correlation were conducted using SPSS v26. Results indicated that students reported moderately high acceptance of AI for learning but low perceptions of fairness, transparency, and accountability. Transparency emerged as the most critical concern, with 45-50% of students reporting limited understanding of AI decision-making processes. Correlation analysis revealed significant positive relationships between all three FTA dimensions and student acceptance. The findings suggest that while perceived usefulness drives initial adoption, ethical concerns may hinder sustainable use. The study recommends that Pakistani HEIs implement bias-free AI systems, provide explainable AI interfaces, and establish clear accountability structures to build student trust. This study contributes to AI ethics literature in the Pakistani context and provides implications for policymakers and university administrators.