Economics at your fingertips  

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

Kazuyuki Motohashi ()

Discussion papers from Research Institute of Economy, Trade and Industry (RIETI)

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.

Pages: 22 pages
Date: 2020-02
New Economics Papers: this item is included in nep-ipr and nep-tid
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link) (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in Discussion papers from Research Institute of Economy, Trade and Industry (RIETI) Contact information at EDIRC.
Bibliographic data for series maintained by TANIMOTO, Toko ().

Page updated 2023-06-15
Handle: RePEc:eti:dpaper:20010