A COMPARATIVE VIEW OF ARTIFICIAL INTELLIGENCE REGULATION IN THE EUROPEAN UNION, JAPAN, PEOPLE’S REPUBLIC OF CHINA, AND THE UNITED STATES OF AMERICA

Abstract

The Article analyzes the divergent regulatory architectures governing artificial intelligence across the European Union, the United States, Japan, and the People’s Republic of China, tracing their evolution from early data-protection frameworks to contemporary system-level governance. The Article demonstrates how the EU’s AI Act operationalizes a comprehensive risk-based regulatory model that imposes ex-ante obligations, categorical prohibitions, and conformity assessments to structure market behavior. The U.S. trajectory is defined by sectoral statutes, oscillating executive priorities, and a persistent absence of federal coherence, producing a permissive environment punctuated by episodic soft-law interventions and subsequent deregulatory shifts under the 2025 administration. Japan advances an innovation-centric, business-led governance model grounded in sector-specific regulation, flexible intellectual property rules, and non-binding ethical guidance. China’s regulatory regime integrates algorithmic licensing, content governance, and mandatory ethical review within a broader security-driven framework characterized by opacity, expansive state discretion, and ideological grounding. Comparative analysis reveals five structural fault lines: transparency and accountability mandates, divergent risk-mitigation rationales, sectoral calibration, data-governance philosophies, and the entanglement of AI policy with national industrial and geopolitical strategy. Efforts at international harmonization, through the Group of 7ca, the Organization of Economic Cooperation and Development, the World Economic Forum, and others, remain non-binding and fragmented. The Article concludes that global convergence is unlikely; regulatory pluralism will define AI governance.