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

Author Name MOTOHASHI Kazuyuki (Faculty Fellow, RIETI)
Creation Date/NO. February 2020 20-E-010
Research Project Digitalization and Innovation Ecosystem: A Holistic approach
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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.