GSTDTAP  > 气候变化
DOI10.1787/7b43b038-en
Measuring the AI content of government-funded R&D projects
Izumi Yamashita; Akiyoshi Murakami; Stephanie Cairns ; and ; Fernando Galindo-Rueda
2021-06-28
出版年2021
国家国际
领域气候变化 ; 资源环境 ; 地球科学
英文摘要

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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来源平台OECD iLibrary
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文献类型科技报告
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/334584
专题气候变化
地球科学
资源环境科学
推荐引用方式
GB/T 7714
Izumi Yamashita,Akiyoshi Murakami,Stephanie Cairns ,et al. Measuring the AI content of government-funded R&D projects,2021.
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