Designing an AI-Driven Legislation Framework to Improve Indonesia's Law-Making Transparency and Public Participation - Firdaus Arifin; Cece Suryana; Ihsanul Maarif; Robi Assadul Bahri; Anastasia Wahyu Murbani (Yustisia, 2025)
The legislative process in Indonesia faces persistent challenges, including inefficiency, limited transparency, and minimal public participation. This study examines the integration of AI, particularly Natural Language Processing, into the design of an e-legislation system to address these systemic issues. Employing a normative-empirical legal research methodology, this study combines doctrinal legal analysis with a design science approach to prototype an AI-driven legislative platform. The study reveals that integrating AI, particularly Natural Language Processing, can enhance legal drafting efficiency, improve legislative process transparency, and enable real-time public participation. The proposed AI-driven legislation system can detect redundancies, contradictions, and legal inconsistencies, as well as classify public input to support evidence-based decision-making. The study underscores the importance of explainable AI principles, algorithmic transparency, and participatory feedback mechanisms to uphold democratic legitimacy. Pivotal challenges identified include limited digital infrastructure, the absence of specific legal frameworks for AI in legislation, and risks of bias and privacy violations. The study recommends establishing specific regulations, conducting pilot testing of the prototype system, and fostering multidisciplinary collaboration to ensure AI's ethical, accountable, and inclusive use in Indonesia's law-making process