基于PMC指数模型的中美人工智能政策比较研究

Comparative Study on Artificial Intelligence Policies between China and the United States Based on PMC Index Model

摘要:

人工智能对于科技创新发展具有重要作用,通过政策文本量化研究对比分析中美两国人工智能政策,能够为我国的人工智能政策制定提供参考依据和路径优化建议。本研究基于文本挖掘和PMC指数模型,建立人工智能政策评价指标体系,结合PMC指数值和PMC曲面图,对中美两国人工智能政策文本进行量化评价和对比研究。研究发现,中美两国人工智能政策的总体表现较好,政策协同性较高；中国人工智能政策在政策对象、政策领域以及政策评价等方面要优于美国,而美国的政策在政策内容、保障措施等方面比中国更完善。最后,本研究从保障措施、政策内容与政策领域三个方面提出完善中国人工智能政策的发展对策。

Abstract:

Artificial intelligence plays an important role in the development of science and technology innovation, and the comparative analysis of AI policies in China and the United States through quantitative research on policy texts can provide reference basis and path optimisation suggestions for the formulation of AI policies in China. Based on text mining and PMC index model, this study establishes the AI policy evaluation index system, combines the PMC index value and PMC surface diagram, and carries out quantitative evaluation and comparative research on the AI policy texts of China and the United States. It is found that the overall performance of AI policies in China and the United States is better, and the policy synergy is higher; China"s AI policies are better than those of the United States in terms of policy objects, policy areas, and policy evaluations, while the United States" policies are better than those of China"s in terms of policy content and safeguard measures. Finally, this study proposes development countermeasures to improve China"s AI policies from three aspects: safeguards, policy content and policy areas.