比较四国AI治理机制，推动全球协同安全监管。
Interoperability in AI Safety Governance: Ethics, Regulations, and Standards
- 对比中、韩、新、英四国治理框架，找共性与差异
- 识别法规碎片化与全球协作不足等关键障碍
- 聚焦自动驾驶等三领域，提出可落地的政策建议
本政策报告基于中国、韩国、新加坡和英国的国家研究，识别出促进AI安全治理互操作性的有效工具与主要障碍。报告提出实用建议，以支持兼具全球视野与本地适应性的治理生态。互操作性是AI治理的核心目标，对降低风险、促进创新、增强竞争力、推动标准化及建立公众信任至关重要。然而，制度性缺口（如法规分散、缺乏全球协调）与概念性缺口（如全球南方参与有限）持续阻碍进展。报告聚焦自动驾驶、教育和跨境数据流动三大高风险领域，比较四国在伦理、法律和技术框架上的异同，识别出趋同、分歧与潜在协同点，并提出符合《全球数字契约》及联合国相关决议的政策建议。分析涵盖七大要素：目标、监管机构、伦理、约束措施、适用框架、技术标准与关键风险。
原文摘要 · Abstract (English)
This policy report draws on country studies from China, South Korea, Singapore, and the United Kingdom to identify effective tools and key barriers to interoperability in AI safety governance. It offers practical recommendations to support a globally informed yet locally grounded governance ecosystem. Interoperability is a central goal of AI governance, vital for reducing risks, fostering innovation, enhancing competitiveness, promoting standardization, and building public trust. However, structural gaps such as fragmented regulations and lack of global coordination, and conceptual gaps, including limited Global South engagement, continue to hinder progress. Focusing on three high-stakes domains - autonomous vehicles, education, and cross-border data flows - the report compares ethical, legal, and technical frameworks across the four countries. It identifies areas of convergence, divergence, and potential alignment, offering policy recommendations that support the development of interoperability mechanisms aligned with the Global Digital Compact and relevant UN resolutions. The analysis covers seven components: objectives, regulators, ethics, binding measures, targeted frameworks, technical standards, and key risks.
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