AI-Based Public Service Transformation: An Analysis of Algorithmic Bias Risks and Digital Government Accountability in ASEAN - Adelia Idil; Huda Alimuddin (Asian Digital Governance Problems, 2024)
Purpose: This study examines the risks of algorithmic bias and the challenges of digital government accountability in AI-based public service transformation across ASEAN countries. The research focuses on how governance structures, institutional capacity, and citizen participation influence the ethical implementation of AI in public administration. Subjects and Methods: The study employed a qualitative comparative multi-case study approach involving Singapore, Indonesia, Malaysia, Thailand, and the Philippines. Data were collected through semi-structured interviews with 25 participants, policy document analysis, and comparative case studies. Thematic analysis using NVivo 14 was applied to identify patterns related to algorithmic bias, accountability mechanisms, and public trust. Results: The findings reveal that algorithmic bias remains a major challenge due to unequal datasets, fragmented regulation, and weak institutional oversight. Countries with stronger governance systems demonstrated higher transparency and accountability in AI implementation. Public trust was strongly influenced by citizen participation and transparency practices. Conclusions: Ethical governance, institutional coordination, and inclusive participation are essential to ensure fair, transparent, and accountable AI-based public services in ASEAN countries.