Adaptive Criminal Justice Governance For Artificial Intelligence-Driven Crime In Indonesia

Abstract

Artificial intelligence (AI) changes the conditions under which criminal conduct is planned, executed, concealed, and investigated. Its significance lies not only in enabling new forms of offending but also in distributing relevant actions and information across users, developers, deployers, platforms, and transnational infrastructures. This article examines how Indonesian criminal justice can respond to AI-mediated crime without weakening legality, culpability, due process, and human rights. It employs normative legal research through statutory, conceptual, and functional-comparative approaches, analysing Indonesian criminal law, electronic information regulation, personal data protection, international AI and cybercrime instruments, and selected governance approaches. The analysis identifies five interconnected deficits: normative fragmentation, distributed attribution, synthetic-evidence vulnerability, jurisdictional dispersion, and institutional adaptation lag. In response, the article develops Adaptive Criminal Justice Governance (ACJG), an ecosystem-centred framework organised around three governance layers normative, institutional, and technological-network—and six operational pillars. Its original analytical contributions are distributed attribution, chain of provenance, constrained adaptability, and continuous institutional learning. Distributed attribution uses control, knowledge, foreseeability, and contribution as investigative and analytical dimensions, not as substitute elements of criminal offences. Chain of provenance supplements chain of custody by tracing the creation and transformation of digital objects before and after acquisition. The article argues that criminal justice should preserve a stable normative core while adapting institutional capabilities under enforceable rights-based constraints. For Indonesia, the priority is therefore integrated institutional capacity and evidentiary reliability, rather than automatic expansion of technology-specific criminal offences.