By analyzing the patent applications of artificial intelligence technology inventions in 31 provinces and cities in China from 2012 to 2021, this paper discusses the characteristics of artificial intelligence technology innovation output, and uses the time series analysis method to conduct research to accurately describe the current situation of China's artificial intelligence technology innovation output, and provides scientific decision support for the development of artificial intelligence technology in China. Through the analysis of the innovation output and network characteristics of AI technology cooperation, it is found that the innovation output of AI technology in China is increasing in absolute and relative differences. About a quarter of provinces have patent cooperation below the average; Finally, based on the analysis results, from the perspectives of innovation subjects and innovation networks, this paper proposes countermeasures and suggestions to improve the output level of artificial intelligence technology innovation and promote the coordinated development of industry, university and research.

Jiayi Wu. Research on innovation output and characteristics of industry-university-research cooperation in artificial intelligence technology in Chinese provinces. The Frontiers of Society, Science and Technology (2024), Vol. 6, Issue 6: 86-94. https://doi.org/10.25236/FSST.2024.060614.

[1] Liu G W , Li S , Chen Y J ,et al. Integration of production-university-research based on artificial intelligence for technological innovation and transformation in gastrointestinal surgery[J].Zhonghua wei chang wai ke za zhi = Chinese journal of gastrointestinal surgery, 2020, 23(6):557-561.DOI:10.3760/cma.j.cn.441530-20200305-00118.

[2] Maggioni M A, Uberti T E. International networks of knowledge flows: An econometric analysis [J].Papers on Economics & Evolution, 2006, 28 (273): 709-751.

[3] Sebastian Zander, Simon Trang, Lutz M. Kolbe. Drivers of network governance: a multitheoretic perspective with insights from case studies in the German wood industry [J]. Journal of Cleaner Production, 2016110 (Jan. 1): 109-120.

[4] Xu Xiaoyi, Yang Liying. Characteristics analysis of subject knowledge flow network based on co-authored papers: A case study of Medicinal Chemistry [J]. Library and Information Work, 2015, 59(1): 89-98. 

[5] Liu Fengchao, Ma Rongkang, Jiang Nan. Evolution path of industry-university-research patent cooperation network based on -985 universities [J]. China Soft Science, 2011(07):178-192. 

[6] Liu Qiong, Liu Guifeng, Liu Hongguang, et al. Analysis of industry-University-research collaborative innovation activities in Tsinghua University: Based on patent cooperation network [J]. Information Science, 2016, 34(01):120-124+129.