Quantitative mapping of the evolution of AI policy distribution, targets and focuses over three decades in China

Chao Yang and Cui Huang

Technological Forecasting and Social Change, 2022, vol. 174, issue C

Abstract: Artificial intelligence (AI) technology policy plays a critical role to steer its applications to broadly relevant endpoints, and contributes to critical governance of innovations by governments, industry and society at large. In this paper, we adopt a bibliometrics-based research framework to characterize the development and evolution of China's AI policy. The framework integrates bibliometric methods, semantic analysis, and network analysis for identifying core policy elements and their evolution in the AI policy process. Specifically, we first collect China's central-level AI-related policies and identify four stages of its evolution based on policy-issuing frequency, policy trends, and core policy issuing time nodes. We then identify the core policies, core institutions, and core policy targets in each stage. Then we explore the policy issuing trends, policy distribution changes, and evolution of policy targets. Finally, patterns and characteristics of the policy process are identified, and trends are predicted. We used the PKULaw database to collect the policy-relevant data on AI in China, and the time frame is from 1990 to 2019. Our findings and the reported quantitative map might usefully inform AI policy in China and elsewhere around the world. It could also help broader stakeholder engagement in policy discussions on AI technology, industry and society.

Keywords: Artificial intelligence (AI); China's policy; Bibliometrics; Policy evolution; Policy documents (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162521006211
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:174:y:2022:i:c:s0040162521006211

DOI: 10.1016/j.techfore.2021.121188

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().