以我国公布的30份人工智能政策文本为样本，基于政策工具和PMC政策评价模型，采用文本挖掘及内容分析法，对我国当前人工智能政策文本进行量化分析。结果发现，我国人工智能政策中的需求型政策工具需进一步加强，环境型政策工具结构有待调整；通过对处于不同评价等级、针对不同产业发展政策文本的PMC指数进行比较，识别出影响我国人工智能政策文本评价等级的具体变量。最后，结合我国人工智能研究前沿趋势分析，探寻未来政策制定方向，为后续人工智能政策的制定和修改提供具体、可操作性建议。
In this paper, 30 artificial intelligence policy texts published in China are taken as samples. Based on policy tools and PMC policy evaluation model, text mining and content analysis are adopted to conduct quantitative analysis on the current artificial intelligence industrial policy texts in China. It is found that demand-type policy tools of artificial intelligence industrial policy in China need to be further strengthened, and the structure of environment-type policy tools needs to be adjusted scientifically. Through comparative analysis of PMC indexes of policy texts at different evaluation levels and aiming at the development of different industries, the specific variables affecting the evaluation level of artificial intelligence policy texts in China were identified. Finally, combining with the cutting-edge trend analysis of artificial intelligence research in China, this paper explores the direction of future policy making, and provides specific and operational suggestions for the subsequent formulation and modification of artificial intelligence policies.
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