Digital Rulemaking: Artificial Intelligence Capabilities and Conceptual Issues in Regulatory Impact Assessment

Abstract

This article explores the role and potential of artificial intelligence in improving Regulatory Impact Assessment (RIA) within the framework of digital rulemaking. The study provides a theoretical and conceptual analysis of AI applications throughout the legislative drafting process, including problem identification, assessment of socio-economic impacts, automated detection of legal inconsistencies and corruption risks in draft legislation, and AI-assisted processing of public consultation data through content and sentiment analysis. The article also examines key challenges associated with integrating AI into RIA, such as data quality, algorithmic transparency (the "black box" problem), and legal accountability for AI-assisted decisions. The study concludes that a hybrid intelligence model, combining the analytical capabilities of artificial intelligence with human legal expertise, represents the most effective approach to developing evidence-based, transparent, and high-quality legislation while enhancing the effectiveness of regulatory policy and public governance in the digital era.