From Science to Politics: Insights from the Climate Change Response Model for Artificial Intelligence Governance

人工智能全球治理前景分析

Abstract

The serious risks arising from the rapid development of artificial intelligence (AI) are becoming increasingly prominent, and its governance has become a major contemporary challenge of common concern to the global academic community, governments, and international organizations. However, a breakthrough governance solution has yet to be formed. By analyzing climate change as a typical case of global governance, this study finds similarities between AI and climate change in many aspects, such as the process of risk recognition and governance response. Relevant historical experiences can provide a reference paradigm for AI governance. Using comparative and historical research methods, this study traces and compares the development, evolution, and governance processes of both. The study finds that climate governance follows a gradual global collaborative governance path of "scientific consensus-driven - political agenda response"; while AI has accelerated the formation of a broad consensus from risk identification to global co-governance, and is gradually shifting towards the political agenda and taking related actions. In view of this, we can fully draw on the valuable experience of global climate change governance, negotiate the establishment of a similar international AI governance institution, reach a global AI agreement, and formulate a global governance framework and standards to unify action plans and effectively promote global AI governance.