Abstract: The serious risks derived from the rapid development of artificial intelligence have become increasingly prominent, and its governance issue has developed into a major problem of The Times that is of common concern to the global academic community, governments and international organizations, but no breakthrough governance plan has yet been formed. Through the analysis of climate change, a typical case of global governance, it is found that the two have convergence in many aspects such as risk understanding process and governance response path, and relevant historical experience will provide a reference paradigm for AI governance. Using the comparative research method and the historical research method, the development, evolution and governance process of the two are sorted out and compared. The study found that climate governance follows the path of progressive global collaborative governance driven by scientific consensus and responsive to political agenda. Artificial intelligence has accelerated the formation of a broad consensus, from risk identification to global co-governance, and is gradually moving to the political agenda and related actions. In view of this, we can fully learn from the valuable experience of global governance on climate change, negotiate the establishment of a similar artificial intelligence international governance body, reach a global agreement on artificial intelligence, formulate a global governance framework and standards, and unify action plans to effectively promote artificial intelligence global governance.

摘要： 人工智能高速发展所衍生的严重风险日益凸显，其治理议题已发展为全球学界、各国政府和国际组织共同关注的重大时代难题，但目前尚未形成突破性的治理方案。通过剖析气候变化这一全球治理典型案例，发现两者在风险认识历程及治理应对路径等诸多方面具有趋同性，相关历史经验将为人工智能治理提供参考范式。运用比较研究法和历史研究法，梳理和对比两者的发展、演化及治理历程。研究发现，气候治理遵循"科学共识驱动-政治议程响应"的渐进式全球协同治理路径；人工智能则加速形成了从风险识别到全球共治的广泛共识，正逐步转向政治议程并展开相关行动。鉴于此，可充分汲取借鉴气候变化全球治理的宝贵经验，协商成立类似的人工智能国际治理机构，达成人工智能全球协定，制定全球治理框架和标准规范，以此统一行动方案从而有效推进人工智能全球治理。