AI Ethics in Indonesian Higher Education: A Systematic Review of Algorithmic Bias, Privacy, and Accountability - Yomi Agung Susanto; Eko Hariadi; Lilik Anifah; Ratna Suhartini; Purwoko Ajie (Register: Jurnal Ilmiah Teknologi Sistem Informasi, 2026)
Artificial Intelligence (AI) is increasingly integrated into higher education to enhance personalised learning, automate assessment, and improve institutional efficiency. However, its rapid adoption also raises ethical concerns related to algorithmic bias, data privacy, and accountability, particularly in Indonesia, where regulatory frameworks and digital infrastructure remain underdeveloped. Despite growing global discussions on AI ethics, limited studies have systematically examined these challenges within Indonesian higher education. This study analyses the ethical implications of AI integration by focusing on algorithmic fairness, data privacy, and governance accountability. Employing a narrative review approach supported by the PRISMA 2020 framework, this study systematically reviews 56 studies retrieved from the Scopus database between 2021 and 2025. Article screening was conducted using Covidence, while VOSviewer was utilised to identify research trends and thematic gaps. The findings reveal three major ethical concerns: (1) algorithmic bias in AI-driven assessment and admissions systems; (2) risks to data privacy and student surveillance associated with learning analytics; and (3) limited transparency and accountability in AI-based decision-making. The study further identifies significant gaps in Indonesia’s policy readiness and institutional governance. As its contribution, this study proposes a culturally grounded approach to AI governance and recommends the development of a National AI in Education Ethics Charter to support responsible and equitable AI integration in higher education.