Artificial Intelligence Governance and Legal Accountability in Indonesia: Strengthening Regulatory Frameworks for Algorithmic Decision-Making

Abstract

The rapid adoption of artificial intelligence (AI) in Indonesia has generated significant legal challenges concerning regulatory adequacy, accountability, transparency, human oversight, and protection of individual rights. The absence of a comprehensive AI-specific legal framework has resulted in regulatory fragmentation across electronic systems, personal data protection, consumer protection, and sectoral regulations, creating uncertainty regarding responsibility for AI-assisted decisions. This study examines the current regulation of AI in Indonesia, analyzes legal accountability problems arising from AI-based decision-making, and formulates a governance model capable of strengthening responsible AI deployment. This research employs a normative juridical method using statutory, conceptual, and comparative approaches to analyze Indonesian legislation, regulatory instruments, relevant legal principles, scholarly literature, and comparative AI governance frameworks. The findings demonstrate that existing Indonesian regulations provide important legal foundations for governing AI-related activities but remain insufficient to address algorithmic transparency, risk classification, human oversight, lifecycle accountability, and liability for harmful outcomes. The study further finds that responsibility should not be attributed to AI systems as autonomous legal actors but distributed among developers, providers, deployers, and human decision-makers according to their respective levels of control, knowledge, and capacity to prevent harm. The proposed governance model integrates risk-based regulation, algorithmic accountability, meaningful transparency, human oversight, institutional supervision, auditing, and effective remedies. This framework can strengthen legal certainty, protect fundamental rights, and support responsible technological innovation within Indonesia’s rule-of-law framework.