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Measuring the AI content of government-funded R&D projects: A proof of concept for the OECD Fundstat initiative

Author

Listed:
  • Izumi Yamashita
  • Akiyoshi Murakami
  • Stephanie Cairns
  • Fernando Galindo-Rueda

Abstract

This report presents the results of a proof of concept for a new analytical infrastructure (“Fundstat”) for analysing government funding of R&D at the project level, exploiting the wealth of text-based information about funded projects. Reflecting the growth in popularity of artificial intelligence (AI) and the OECD Council Recommendation on AI’s emphasis on R&D investment, the report focuses on analysing government investments into AI-related R&D. Using text mining tools, it documents the creation of a list of key terms used to identify AI-related R&D projects contained in 13 funding databases from eight OECD countries and the EU, provides estimates for the total number and volume of government R&D funding, and characterises their AI funding portfolio. The methods and findings developed in this study also serve as a prototype for a new distributed mechanism capable of measuring and analysing government R&D support across key OECD priority areas and topics.

Suggested Citation

  • Izumi Yamashita & Akiyoshi Murakami & Stephanie Cairns & Fernando Galindo-Rueda, 2021. "Measuring the AI content of government-funded R&D projects: A proof of concept for the OECD Fundstat initiative," OECD Science, Technology and Industry Working Papers 2021/09, OECD Publishing.
    • Handle: RePEc:oec:stiaaa:2021/09-en
    DOI: 10.1787/7b43b038-en
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    Cited by:

    1. Diego Chavarro & Jaime Andrés Perez-Taborda & Alba Ávila, 2022. "Connecting brain and heart: artificial intelligence for sustainable development," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7041-7060, December.
    2. Giordano, Vito & Spada, Irene & Chiarello, Filippo & Fantoni, Gualtiero, 2024. "The impact of ChatGPT on human skills: A quantitative study on twitter data," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    3. Rathi, Sawan & Majumdar, Adrija & Chatterjee, Chirantan, 2024. "Did the COVID-19 pandemic propel usage of AI in pharmaceutical innovation? New evidence from patenting data," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    4. Farhat Chowdhury & Albert N. Link & Martijn Hasselt, 2022. "Public support for research in artificial intelligence: a descriptive study of U.S. Department of Defense SBIR Projects," The Journal of Technology Transfer, Springer, vol. 47(3), pages 762-774, June.

    More about this item

    Keywords

    artificial intelligence; government funding; research and development;
    All these keywords.

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