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Comparative Analysis between International Research Hotspots and National-Level Policy Keywords on Artificial Intelligence in China from 2009 to 2018

Author

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  • Jie Gao

    (School of Public Policy and Management, Tsinghua University, Beijing 100084, China
    Center for Science, Technology & Education Policy, Tsinghua University, Beijing 100084, China)

  • Xinping Huang

    (School of Public Policy and Management, Tsinghua University, Beijing 100084, China
    Center for Science, Technology & Education Policy, Tsinghua University, Beijing 100084, China)

  • Lili Zhang

    (School of Public Policy and Management, Tsinghua University, Beijing 100084, China
    Center for Science, Technology & Education Policy, Tsinghua University, Beijing 100084, China)

Abstract

In the last decade, artificial intelligence (AI) has undergone many important developments in China and has risen to the level of national strategy, which is closely related to the areas of research and policy promotion. The interactive relationship between the hotspots of China’s international AI research and its national-level policy keywords is the basis for further clarification and reference in academics and political circles. There has been very little research on the interaction between academic research and policy making. Understanding the relationship between the content of academic research and the content emphasized by actual operational policy will help scholars to better apply research to practice, and help decision-makers to manage effectively. Based on 3577 English publications about AI published by Chinese scholars in 2009–2018, and 262 Chinese national-level policy documents published during this period, this study carried out scientometric analysis and quantitative analysis of policy documents through the knowledge maps of AI international research hotspots in China and the co-occurrence maps of Chinese policy keywords, and conducted a comparative analysis that divided China’s AI development into three stages: the initial exploration stage, the steady rising stage, and the rapid development stage. The studies showed that in the initial exploration stage (2009–2012), research hotspots and policy keywords had a certain alienation relationship; in the steady rising stage (2013–2015), research hotspots focused more on cutting-edge technologies and policy keywords focused more on macro-guidance, and the relationship began to become close; and in the rapid development stage (2016–2018), the research hotspots and policy keywords became closely integrated, and they were mutually infiltrated and complementary, thus realizing organic integration and close connection. Through comparative analysis between international research hotspots and national-level policy keywords on AI in China from 2009 to 2018, the development of AI in China was revealed to some extent, along with the interaction between academics and politics in the past ten years, which is of great significance for the sustainable development and effective governance of China’s artificial intelligence.

Suggested Citation

  • Jie Gao & Xinping Huang & Lili Zhang, 2019. "Comparative Analysis between International Research Hotspots and National-Level Policy Keywords on Artificial Intelligence in China from 2009 to 2018," Sustainability, MDPI, vol. 11(23), pages 1-18, November.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:23:p:6574-:d:289411
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    References listed on IDEAS

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    2. Yang, Chao & Huang, Cui, 2022. "Quantitative mapping of the evolution of AI policy distribution, targets and focuses over three decades in China," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    3. Na Liu & Philip Shapira & Xiaoxu Yue, 2021. "Tracking developments in artificial intelligence research: constructing and applying a new search strategy," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3153-3192, April.
    4. Muhammad Tanveer & Shafiqul Hassan & Amiya Bhaumik, 2020. "Academic Policy Regarding Sustainability and Artificial Intelligence (AI)," Sustainability, MDPI, vol. 12(22), pages 1-13, November.
    5. Miltiadis D. Lytras & Anna Visvizi, 2021. "Artificial Intelligence and Cognitive Computing: Methods, Technologies, Systems, Applications and Policy Making," Sustainability, MDPI, vol. 13(7), pages 1-3, March.
    6. Jie Gao & Wu Zhang & Chunbaixue Yang & Rui Wang & Shuai Shao & Jiawei Li & Limiao Zhang & Zhijian Li & Shu Liu & Wentao Si, 2022. "Comparative Study on International Research Hotspots and National-Level Policy Keywords of Dynamic Disaster Monitoring and Early Warning in China (2000–2021)," IJERPH, MDPI, vol. 19(22), pages 1-19, November.
    7. Ricardo Arencibia-Jorge & Rosa Lidia Vega-Almeida & José Luis Jiménez-Andrade & Humberto Carrillo-Calvet, 2022. "Evolutionary stages and multidisciplinary nature of artificial intelligence research," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5139-5158, September.

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