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Scientific Information Research

Keywords

artificial intelligence, policy evaluation, PMC index model

Abstract

[Purpose/significance]The quantitative evaluation of existing effective artificial intelligence (AI) policies aims to provide reference for government department to formulate scientific and reasonable AI policies and promote the development of AI. [Method/process]Taking 10 AI policies in the Yangtze River Delta region from 2015 to 2024 as the research samples, the text mining method is used to construct the evaluation index system of AI policies in the Yangtze River Delta region, and conduct quantitative evaluation by combining the PMC index model. [Result/conclusion]The study found that from a macro policy text perspective, the average PMC index of the 10 AI policy samples in the Yangtze River Delta region was 7.11, indicating that the overall policy design was scientifically rational. From a micro policy text perspective, there were significant differences in the levels of AI policy texts in the Yangtze River Delta region. Based on the research conclusions, targeted policy improvement suggestions are proposed in terms of expanding the scope of policy targets, establishing a policy evaluation system, adjusting policy directions, and implementing policies tailored to local conditions.

First Page

13

Last Page

22

Submission Date

June 2024

Revision Date

August 2024

Publication Date

4-1-2025

Digital Object Identifier (DOI)

10.19809/j.cnki.kjqbyj.2025.02.002

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