分析生成式人工智能（Generative Artifical Intelligence，GenAI）政策法规的治理效能，既能促进发展人工智能新质生产力与丰富生成式人工智能治理的学理研究，又能助力提升信息治理效能与深化国家网络空间治理水平。文章首先依据相关理论，从政府治理、资源禀赋、技术环境三个维度，分析影响生成式人工智能政策法规治理效能的因素；随后以30个国家生成式人工智能政策法规为样本，采用fsQCA方法，借助PMC指数评价结果，探究提升生成式人工智能政策法规治理效能的潜在路径。研究表明，政策法规质量、政府行为、风险资金投入、人工智能治理能力、公众主体活动、人工智能安全机制是影响生成式人工智能政策法规治理效能的六大因素。最后提出技术资源驱动、政策主体配合、政府多元主体协调是提升生成式人工智能政策法规治理效能的潜在组态路径。

Analyzing the governance efficacy of generative AI policies and regulations can not only facilitate the development of GenAI-driven new quality productive forces and enrich theoretical research on generative AI governance, but also help enhance information governance effectiveness and advance national cyberspace governance capabilities. Drawing on relevant theoretical frameworks, this paper first analyzes the factors influencing the governance efficacy of generative AI policies and regulations from three dimensions: government governance, resource endowment, and technological environment. Subsequently, this paper takes the policies and regulations of generative AI in 30 countries as samples, employs the fsQCA method and utilizes PMC index evaluation results to explore potential pathways for enhancing the governance efficacy of generative AI policies and regulations. The findings demonstrate that the governance efficacy of generative AI policies and regulations is primarily influenced by six critical factors: the quality of policies and regulations, government conduct, risk capital investment, AI governance capacity, public subject activities, and AI safety mechanisms. Finally, the paper proposes three synergistic configuration paths to upgrade governance efficacy: technology-resource-driven path, policy-actors coordination, and government-led multi-subject coordination.