EY+人工智能的全球监管格局-英-21页_4mb
报告摘要
Global AI Regulatory Trends: Key Findings
Context
- Five key regulatory trends are identified to enhance trust in AI use.
- Jurisdictions studied include Canada, China, EU, Japan, Korea, Singapore, UK, and US.
- OECD principles serve as a benchmark for AI governance.
Five Key Regulatory Trends
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Adherence to OECD Principles:
- OECD principles guide AI regulation, emphasizing human rights, transparency, and robust risk management.
- Jurisdictions like EU and Canada are implementing mandatory rules based on these principles.
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Risk-Based Approach:
- AI systems are categorized into risk levels with proportional compliance requirements.
- Examples include the EU’s AI Act and Canada’s AI and Data Act.
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Sector-Specific Regulations:
- Regulations address unique risks in specific sectors (e.g., financial services, autonomous vehicles).
- Combinations of cross-sectoral and sector-specific approaches are common.
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Integration with Other Policies:
- AI rulemaking intersects with data privacy, cybersecurity, and digital content policies.
- The EU takes a comprehensive approach, while other regions address AI impacts on existing policy areas.
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Use of Regulatory Sandboxes:
- Sandboxes enable controlled testing of AI innovations with reduced regulatory barriers.
- Examples include the UK, Singapore, and EU regulatory sandboxes for AI.
Implications for Policymakers and Companies
For Policymakers
- Ensure interoperability of global regulations to reduce regulatory arbitrage.
- Clarify whether regulations target AI technology or its applications.
- Extend accountability to third-party vendors and address expertise gaps.
For Companies
- Align internal AI governance with jurisdictional regulations.
- Establish robust risk management structures and accountability mechanisms.
- Engage in dialogue with policymakers and leverage regulatory sandboxes for innovation.
This summary outlines the evolving global AI regulatory landscape, highlighting key trends and necessary actions for stakeholders.
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