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Understanding AI Driven Innovation by Linked Database of Scientific Articles and Patents

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  • MOTOHASHI Kazuyuki

Abstract

The linked dataset of AI research articles and patents reveals that substantial contributions by the public sector are found in 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 in research articles, and propriety technology that is protected by patents, are intertwined in AI development. In addition, the impact of AI, combined with big data and IoT, which are defined as "new" IT innovations, is discussed by comparing it with traditional IT, which only consists of the technological progress of computer hardware and software developments. Both new and traditional IT can be understood by using the framework of GPT (general purpose technology), while the organization of new IT innovation can be characterized as an emergence of multiple ecosystems, instead of being organized in the pattern of platform leadership, found in traditional IT.

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  • MOTOHASHI Kazuyuki, 2018. "Understanding AI Driven Innovation by Linked Database of Scientific Articles and Patents," Policy Discussion Papers 18017, Research Institute of Economy, Trade and Industry (RIETI).
    • Handle: RePEc:eti:polidp:18017
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    File URL: https://www.rieti.go.jp/jp/publications/pdp/18p017.pdf
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    Cited by:

    1. Thorsten Lammers & Dilek Cetindamar & Maren Borkert, 2021. "A Digital Tale of Two Cities—Observing the Dynamics of the Artificial Intelligence Ecosystems in Berlin and Sydney," Sustainability, MDPI, vol. 13(19), pages 1-19, September.
    2. Alexander Kopka & Dirk Fornahl, 2024. "Artificial intelligence and firm growth — catch-up processes of SMEs through integrating AI into their knowledge bases," Small Business Economics, Springer, vol. 62(1), pages 63-85, January.

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