薛澜：AI治理并非创新对立面，需要回归全球合作

Core Viewpoint - The governance of artificial intelligence (AI) must extend beyond national boundaries due to its cross-border characteristics, impact scope, and systemic risks, making it a significant global challenge [1][6]. Group 1: AI Governance Dimensions - AI governance is a dynamic, multi-dimensional process involving various tools and stakeholders, aimed at preventing potential risks and shaping the development direction and application boundaries of AI [2]. - The governance framework can be categorized into three levels: ethical and value dimensions, policy support and market incentives, and regulation and standards [3][4]. Group 2: Ethical and Value Dimensions - This dimension focuses on fundamental ethical principles that AI systems should adhere to during development and application, including safety, transparency, fairness, and accountability [3]. - Various organizations, including China's AI Governance Expert Committee and the EU, have proposed ethical frameworks to guide responsible AI development [3]. Group 3: Policy Support and Market Incentives - Governance is not only about restrictions but also about shaping and incentivizing AI innovation through government support, including funding, infrastructure, and talent policies [4]. - China's "New Generation AI Development Plan" emphasizes a collaborative innovation path between the state and enterprises, showcasing a policy-driven governance structure [4]. Group 4: Regulation and Standards - Regulation is a crucial component of governance, encompassing laws, technical standards, and compliance assessments [4]. - The EU's AI Act, which categorizes AI systems into different risk levels, serves as a significant example of differentiated regulatory requirements [4]. Group 5: Global Governance Challenges - The differences in technological paths among countries lead to varied governance approaches and challenges in aligning risk perceptions [7]. - The rapid development of AI technology often outpaces the evolution of governance frameworks, resulting in a mismatch between technological advancement and regulatory responses [8]. - The existence of multiple global governance initiatives creates a "mechanism complex" that lacks coordination, leading to inefficiencies and conflicts [9]. - Geopolitical tensions increasingly hinder international cooperation on AI governance, transforming collaborative efforts into competitive projects among a few leading nations [10]. Group 6: Future Directions - Effective AI governance requires cooperation, inclusivity, and legitimacy to address cross-border risks and build public trust [11]. - The governance of AI should be viewed as an integral part of its technological evolution, focusing on risk management, social structure shaping, and market mechanism development [11].