政策工具视角下亚洲地区人工智能法规内容分析

Analysis of the Content of Artificial Intelligence Regulations in Asia from the Perspective of Policy Tools

摘要: 【目的/意义】政策工具是政策目标实现的抓手，从政策工具视角探析亚洲地区人工智能法规特征，对亚洲地区人工智能法规进行分析，为人工智能法规的优化提供参考价值。【方法/过程】在政策工具理论的基础上，运用内容分析的方法，从基本法律政策工具和政策目标两个维度对亚洲地区颁布的121条人工智能法规政策相关文件进行分析。【结果/结论】121个政策文本编号中，在基本政策工具维度上，环境型政策工具有76条，所占比例为62.8%，是占比最高的；其次为供给型政策工具，有29条，占比为23.9%，而需求型政策工具有16条，所占比例为13.2%，是占比最低的。在政策目标维度上，新兴产业新格局政策目标所占比例最高(61条，50.41%)，其次是加快融合应用政策目标(20条，16.53%)，之后是构建科技创新体系政策目标(18条，14.88%)，实施大数据战略政策目标(9条，7.44%)和加快培养高端人才政策目标(7条，5.79%)相对较少，完善网络基础设施政策目标最少(6条，4.69%)。

Abstract: [Purpose/Significance] Policy tools are the starting point for the realization of policy goals, which analyze the characteristics of AI regulations in Asia from the perspective of policy tools, analyze AI regulations in Asia, and provide reference value for optimizing AI regulations. [Method/Process] Based on policy instrument theory, this thesis analyzes 121 AI regulations and policies in Asia from two dimensions: basic legal policy tools and policy objectives. [Results/Conclusions] Among the 121 policy text numbers, environmental policy instruments accounted for the highest proportion (76 items, 62.8%), followed by supply-oriented policy instruments (29 items, 23.9%), and demand-based policy instruments accounted for the lowest proportion (16 items, 13.2%). In terms of policy objectives, the policy objectives of the new pattern of emerging industries accounted for the highest proportion (61 items, 50.41%), followed by the policy objectives of accelerating the integration and application (20 items, 16.53%), followed by the policy objectives of building a scientific and technological innovation system (18 items, 14.88%), the implementation of big data strategic policy objectives (9 items, 7.44%) and the policy objectives of accelerating the cultivation of high-end talents (7 items, 5.79%), and the policy objectives of improving network infrastructure (6 items, 4.69%) were relatively few.