关于模型治理，中美欧的差异与共识

Core Viewpoint - The article discusses the evolving landscape of artificial intelligence governance, particularly focusing on the governance of general-purpose and frontier models in the US, EU, and China, highlighting their distinct approaches and regulatory frameworks [2][10]. Group 1: EU Governance Approach - The EU has established a complex risk governance framework categorizing AI systems into four risk levels: prohibited, high-risk, limited-risk, and minimal-risk, with stricter regulations for higher-risk categories [4]. - The EU's governance mechanism for general models distinguishes between those with and without "systemic risk," requiring all providers to disclose technical documentation and training summaries, while those with systemic risk must undergo model assessments and report significant incidents [5]. - The EU's framework is characterized by overlapping standards for models and applications, leading to a burdensome regulatory environment that may hinder innovation, prompting the EU Commission to push for simplification of related regulations [6]. Group 2: US Governance Approach - California has adopted a lighter regulatory approach with the signing of the "Frontier AI Transparency Act" (SB 53), focusing on self-regulation and limiting the scope of obligations for model developers [6]. - SB 53 targets "frontier developers" using models with over 10^26 FLOPs, with additional criteria for larger developers, thus narrowing the regulatory scope compared to the EU's broader approach [6]. - The obligations under SB 53 are minimal, primarily requiring basic transparency regarding website information and intended use, contrasting sharply with the EU's extensive documentation requirements [6]. Group 3: China's Governance Approach - China's governance strategy is application-driven, focusing on real-world issues and extending regulations from application services to model governance [7][8]. - The country has established a regulatory framework for algorithm governance, which has laid the groundwork for model governance, addressing risks associated with algorithmic recommendations and deep synthesis technologies [8]. - China's governance framework emphasizes practical measures for risk identification and management, categorizing risks into endogenous, application, and derivative risks, thus providing a clear delineation of responsibilities [9]. Group 4: Commonalities and Future Directions - Despite differing backgrounds and regulatory obligations, the US, EU, and China share a tendency towards "flexible governance" and industry-led initiatives, allowing for greater compliance autonomy [11]. - All three regions are exploring the establishment of assessment ecosystems to address uncertainties in model capabilities, with suggestions for community-driven evaluation mechanisms [11]. - Transparency has emerged as a core governance tool across the three regions, facilitating maximum control with minimal constraints, thereby fostering innovation while ensuring accountability [12].