Measuring the AI content of government-funded R&D projects

: a proof of concept for the OECD Fundstat initiative

Autor(es):
Yamashita, Izumi
Organización de Cooperación y Desarrollo Económico
Series OECD Science, Technology and Industry Working PapersEditor: París : OECD Publishing, 2021Descripción: 106 p. : gráf. ; 1 documento PDFTipo de contenido: texto (visual)
Tipo de medio: electrónico
Tipo de soporte: recurso en línea
Serie normalizada: OECD Science, Technology and Industry Working PapersTema(s): Inteligencia Artificial | AI | i+D | investigación | desarrollo | financiación gubernamentalRecursos en línea: Acceso al documento

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Resumen: 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.
Lista(s) en las que aparece este ítem: Novedades Julio 2021
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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.

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