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Science and Technology Co-evolution in AI: Empirical Understanding through a Linked Dataset of Scientific Articles and Patents

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  • MOTOHASHI Kazuyuki

Abstract

The linked dataset of AI research articles and patents reveals that a substantial public sector contribution is found for AI development. In addition, the role of researchers who are involved both in publication and patent activities, particularly in the private sector, increased over time. That is, open science that is publicly available through research articles and propriety technology that is protected by patents are intertwined in AI development. In addition, the impact of data science, measured by AI research articles on innovation, is analyzed by patent citation analysis. It is found that patents invented by AI paper authors are more likely to have more forward citations by other applicants (non-self-citation), in wider technology fields (greater generality index). This implies that the nature of general purpose technology (GPT) for data science is elevated by the fact that patent inventors are also involved with scientific activities and published as research authors.

Suggested Citation

  • MOTOHASHI Kazuyuki, 2020. "Science and Technology Co-evolution in AI: Empirical Understanding through a Linked Dataset of Scientific Articles and Patents," Discussion papers 20010, Research Institute of Economy, Trade and Industry (RIETI).
    • Handle: RePEc:eti:dpaper:20010
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    1. David Silver & Julian Schrittwieser & Karen Simonyan & Ioannis Antonoglou & Aja Huang & Arthur Guez & Thomas Hubert & Lucas Baker & Matthew Lai & Adrian Bolton & Yutian Chen & Timothy Lillicrap & Fan , 2017. "Mastering the game of Go without human knowledge," Nature, Nature, vol. 550(7676), pages 354-359, October.
    2. Marina Flamand & F. Manlay & Johannes van Der Pol, 2017. "Patent intelligence for technology intelligence," Post-Print hal-02152019, HAL.
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    Cited by:

    1. Sheer, Lia, 2022. "Sitting on the Fence: Integrating the two worlds of scientific discovery and invention within the firm," Research Policy, Elsevier, vol. 51(7).
    2. Ruilu Yang & Qiang Wu & Yundong Xie, 2023. "Are scientific articles involving corporations associated with higher citations and views? an analysis of the top journals in business research," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5659-5685, October.

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