世界科技研究与发展 ›› 2025, Vol. 47 ›› Issue (2): 247-259.doi: 10.16507/j.issn.1006-6055.2024.09.001 cstr: 32308.14.1006-6055.2024.09.001

• 科技管理与政策 • 上一篇    

中国人工智能政策关联性及区域差异性研究

赵程程   

  1. 上海工程技术大学管理学院
  • 发布日期:2025-04-24
  • 基金资助:
    2022年度教育部人文社会科学研究青年基金“中国企业参与全球人工智能技术创新的位势提升机理及路径选择研究”(22YJCZH254)

Quantitative Research on the Correlation and Regional Differences of China’s Artificial Intelligence Policy

ZHAO Chengcheng   

  1. School of Management, Shanghai University of Engineering Science
  • Published:2025-04-24

摘要: 为了更深入地把握央地人工智能(AI)政策内容,明晰不同区域AI政策布局特点。对中央层面11份AI政策文本内容挖掘和量化分析,构建中国AI政策“主体(Y)-目标(Z)-工具(X)”框架。在此框架下,对地方层面84份AI政策文本内容挖掘和量化分析,比较我国东部、中部、西部、东北地区AI政策“Y-Z”“Y-X”“Z-X”关联的差异性。研究发现,从“Y-Z”关联性上,政府、企业、高校及科研机构在各个政策目标实现过程中均有参与,但政府的参与性相对有限。从“Y-X”关联性上,各地区企业与政策工具之间关联结构类似,均以供给型工具为主,兼顾环境型工具;政府与政策工具的关联性普遍较低,地方政府角色逐渐从主导者演变成引导者;各地区高校及科研机构与政策工具之间关联结构类似,均以供给型工具为主,兼顾需求型工具。从“Z-X”关联性上,各地区使用政策工具组合较为单一,运用供给型工具用以实现“技术领先”、促进“产业转型”;运用需求型工具用以实现“理论突破”;运用环境型工具用以保障“伦理安全”。

关键词: 人工智能政策;文本挖掘;文本关联;政策主体;政策目标;政策工具

Abstract: In order to have a deeper grasp of the content of artificial intelligence (AI) policies at the central and local levels, and clarify the characteristics of AI policy layout in different regions, the paper mines and quantitatively analyzes the content of 11 AI policy texts at the central level, and constructs a three-dimensional analysis framework of “subject(Y)-goal(Z)-tool(X) ”of China’s AI policy. Under this framework, the content of 84 AI policy texts at the local level was mined and quantitatively analyzed, and the differences in the association of “Y-Z”“Y-X” and “Z-X ” of AI policies in the eastern, central, western and northeastern regions of China were compared. The results show that in terms of “Y-Z” correlation, the government, enterprises, universities and scientific research institutions are all involved in the realization of various policy goals, but the participation of the government is relatively limited. In terms of “Y-X” relevance, the correlation structure between enterprises and policy instruments in each region is similar, and all of them are mainly supply-oriented tools, taking into account environment-oriented tools. The correlation between the government and policy tools is generally low, and the role of local governments has gradually evolved from a leader to a guide. The relationship structure between universities and scientific research institutions and policy instruments in different regions is similar, and all of them are mainly supply-oriented tools, taking into account demand-oriented tools. In terms of “Z-X” relevance, the combination of policy tools used in each region is relatively simple, and supply-oriented tools are used to achieve “technology leadership” and promote “industrial transformation”. the use of demand-based tools to achieve “theoretical breakthroughs”; We use environment-based tools to ensure “ethical safety”.

Key words: Artificial Intelligence Policy; Text Mining; Text Relevance; Policy Participants; Policy Objectives; Policy Tool