2. European Union AI Regulatory Trends
3. US Regulations: Collision of Global Regulatory Paradigms
EU AI regulation: 2019 "Ethics Guidelines for Trustworthy AI" — three principles: Lawful (complying with all applicable laws), Ethical (aligned with human-centered values including autonomy, harm prevention, fairness, explainability), Robust (socially and technically resilient). Seven key requirements: Human Agency & Oversight; Technical Robustness & Safety; Privacy & Data Governance; Transparency; Diversity, Non-discrimination & Fairness; Environmental & Societal Well-being; Accountability. EU AI Act (2024): risk-based classification — Unacceptable Risk (banned: social scoring, real-time biometric surveillance, AI manipulating human behavior); High Risk (regulated with requirements: AI in critical infrastructure, education, employment, essential services, law enforcement, border management, justice); Limited Risk (transparency obligations); Minimal Risk (free use). Key High Risk obligations: conformity assessment; risk management system; data governance documentation; human oversight; accuracy and robustness standards; logging and traceability; transparency to users. The GDPR parallel: AI Act is positioned as GDPR for AI — the GDPR set global standards for data protection; EU expects AI Act to similarly shape global AI governance norms. Extraterritorial reach: applies to any AI system affecting EU persons regardless of where the developer is located. US AI regulation: no comprehensive federal AI law; sector-specific approaches (FDA for medical AI, SEC for financial AI, NHTSA for autonomous vehicles); Biden executive order (October 2023) — safety testing requirements, watermarking deepfakes, sector-specific guidance; Trump executive order (2025) — rescinded Biden''s order; deregulatory approach emphasizing American AI leadership; federal preemption of state AI regulations. US vs EU comparison: EU prioritizes precautionary, rights-based approach ("AI must be proven safe before deployment"); US prioritizes innovation, competitiveness ("AI should be deployed unless proven harmful"); the divergence creates regulatory fragmentation for global AI companies requiring different product configurations for EU and US markets.
