Measuring the AI content of government-funded R&D projects : A proof of concept for the OECD Fundstat initiative / Izumi Yamashita ... [et al]
Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: OECD Science, Technology and Industry Working Papers ; no.2021/09Publisher: Paris : OECD Publishing, 2021Description: 1 Online-Ressource (105 p.)Subject(s): DOI: DOI: 10.1787/7b43b038-enOnline resources: Summary: 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.PPN: PPN: 1770753591Package identifier: Produktsigel: ZDB-13-SOC | ZDB-13-SOC-ebookNo physical items for this record