Three AI Regulatory Philosophies Compared
The Comparison
The EU, China, and US each approach AI regulation from fundamentally different starting assumptions, differences that reflect deeper cultural and political worldviews.
EU: Centralized Prevention
Philosophy: Prohibit unless explicitly permitted.
The EU AI Act creates a comprehensive risk classification system enforced through a new centralized AI Office. High-risk systems require conformity assessments before deployment. The approach assumes centralized expertise can anticipate and prevent harms.
Strengths: Systematic, predictable, focused on prevention. Weaknesses: May stifle innovation, slow to adapt, relies on regulators correctly anticipating risks.
US: Decentralized Permission
Philosophy: Permit unless explicitly prohibited.
Executive Order 14110 coordinates existing agencies rather than creating new authority. NIST’s AI Safety Institute brings together academia, industry, and nonprofits. The approach assumes market competition and existing legal frameworks will identify and correct problems.
Strengths: Enables rapid innovation, adapts through case law, leverages distributed expertise. Weaknesses: Harms may occur before correction, enforcement varies, no systematic risk assessment.
California’s SB 1047 represented a state-level experiment with stronger regulation targeting frontier models by computational thresholds.
China: Hybrid Authority
Philosophy: Centralized goals, decentralized execution.
Appears top-down with specific regulations for deepfakes, recommendation algorithms, and generative AI. But enforcement is deliberately uneven, large “National Champions” face full compliance while innovative “Little Giants” get informal latitude.
Strengths: Combines strategic direction with innovation flexibility. Weaknesses: Unpredictable enforcement, favors those with political connections.
Key Differences
| Dimension | EU | US | China |
|---|---|---|---|
| Default stance | Prohibit | Permit | Hybrid |
| Enforcement | Centralized | Distributed | Selective |
| Risk approach | Classification-based | Application-based | Use-case specific |
| Innovation strategy | Sandboxes | Self-regulation | Tiered enforcement |
| Trust placed in | Expert regulators | Markets | Strategic pragmatism |
When Each Applies
EU approach makes sense when:
- Risks are predictable and classifiable
- Prevention is more valuable than rapid deployment
- Regulatory capacity is high
US approach makes sense when:
- Innovation speed matters
- Risks emerge from novel applications
- Legal frameworks can adapt quickly
China approach makes sense when:
- Strategic objectives are clear
- Innovation from smaller players is valued
- Selective enforcement is acceptable
The Takeaway
These frameworks reflect different answers to fundamental questions: Where does expertise reside? When should society accept risk? How should power be distributed?
The “best” approach depends on what you’re optimizing for, and there’s no consensus on that either.
Related: 07-atom—regulatory-philosophy-reflects-trust-in-authority