THE ROLE OF STATUTORY LAW IN REGULATING ARTIFICIAL INTELLIGENCE: BALANCING INNOVATION AND RESPONSIBILITY

Background: Artificial Intelligence (AI) poses profound governance challenges, as its rapid integration across critical sectors exacerbates risks of discrimination, privacy violations, and accountability gaps. Statutory law, which traditionally underpins national legal systems, is proving increasingly insufficient to regulate the ethical, social, and economic implications of AI. Its structural rigidity, coupled with lengthy legislative processes and jurisdictionalfragmentation, renders it ill-equipped to respond to the fast-evolving nature of algorithmic technologies. Consequently, regulatory gaps emerge in high-risk applications such as predictive policing, biometric surveillance, medical diagnostics, and autonomous weapons domains, where errors or biases can lead to irreversible harm. Many existing legal norms were crafted without anticipating the complexity and opacity of machine learning systems, including their potential to operate in ways that defy traditional notions of human intention, liability, and foreseeability. As a resultthere is an urgent need for scholarly engagement with the conceptual and practical tensions between innovation and regulation in the AI context. This includes exploring adaptive legal frameworks, hybrid governance models, and the integration of ethical principles into technological design.Methods: This study employs a comparative legal analysis of AI regulatory frameworks across key jurisdictions (EU, US, China, Brazil, UK), combined with doctrinal research of legislative texts and case law. The methodology integrates a systematic review of primary sources (e.g., EU AI Act, US Algorithmic Accountability Act drafts, China’s GenAI Interim Measures), a qualitative assessment of secondary literature and institutional reports, application of the Issue-Rule-Application-Conclusion framework to evaluate regulatory efficacy, and a cross-jurisdictional examination of enforcement mechanisms and liability standards.Results and conclusions: The analysis reveals statutory law’s critical limitations, jurisdictional divergences in risk classification (e.g., the EU’s ex-ante conformity assessments vs. the US’s sectoral ex-post enforcement), liability fragmentation, and enforcement gaps. Crucially, statutory approaches alone cannot balance innovation promotion with ethical constraints: excessive regulation stifles R and D, while lax frameworks enable societal harm. The study concludes that effective governance requires complementary ethical frameworks that embed transparency, bias auditing, and human oversight; international harmonisation of liability standards and risk protocols; adaptive regulatory sandboxes for real-world testing; and multistakeholder collaboration to design context-sensitive implementations.