Formulating a Responsive Regulatory Architecture for Artificial Intelligence Misuse: A Comparative Legal Politics Study of Indonesia and the Netherlands
Abstract
Introduction: The rapid development of Artificial Intelligence (AI) has created complex legal challenges involving privacy, reputation, accountability, digital evidence, and legal certainty. Indonesia and the Netherlands provide relevant comparative contexts because both are rooted in civil law traditions but demonstrate different approaches to AI governance.
Purposes of the Research: This study aims to analyze the legal politics and regulatory configuration governing AI misuse in Indonesia and the Netherlands, identify Indonesia’s regulatory gaps, and formulate a context-specific reform model based on relevant Dutch practices.
Methods of the Research: This study employs normative legal research using comparative and conceptual approaches. Primary legal materials include Indonesian legislation, the EU Artificial Intelligence Act, the General Data Protection Regulation, Dutch criminal law, and relevant jurisprudence. The materials are analyzed qualitatively through deductive and prescriptive-comparative reasoning using legal politics, responsive law, risk-based regulation, and human-centric AI governance as analytical frameworks.
Results Main Findings of the Research: The findings indicate that Indonesia has a predominantly development-oriented and fragmented regulatory configuration, relying on general and sectoral instruments, while the Netherlands demonstrates a more rights-centred, risk-based, and institutionally coordinated framework. Three gaps are identified in Indonesia: substantive AI-specific norms, institutional oversight, and procedural mechanisms for AI-related evidence and enforcement. This study proposes a Three-Tier Regulatory Architecture comprising AI-specific legislation as a substantive lex specialis, an AI supervisory authority, and adaptive enforcement and evidentiary mechanisms. The model provides a pathway for shifting Indonesia from reactive regulation toward responsive and anticipatory AI governance while maintaining legal certainty, rights protection, and regulatory proportionality.
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