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量化人工智能在科学研究中的应用及潜在益处。

Quantifying the use and potential benefits of artificial intelligence in scientific research.

作者信息

Gao Jian, Wang Dashun

机构信息

Center for Science of Science and Innovation, Northwestern University, Evanston, IL, USA.

Kellogg School of Management, Northwestern University, Evanston, IL, USA.

出版信息

Nat Hum Behav. 2024 Dec;8(12):2281-2292. doi: 10.1038/s41562-024-02020-5. Epub 2024 Oct 11.

Abstract

The rapid advancement of artificial intelligence (AI) is poised to reshape almost every line of work. Despite enormous efforts devoted to understanding AI's economic impacts, we lack a systematic understanding of the benefits to scientific research associated with the use of AI. Here we develop a measurement framework to estimate the direct use of AI and associated benefits in science. We find that the use and benefits of AI appear widespread throughout the sciences, growing especially rapidly since 2015. However, there is a substantial gap between AI education and its application in research, highlighting a misalignment between AI expertise supply and demand. Our analysis also reveals demographic disparities, with disciplines with higher proportions of women or Black scientists reaping fewer benefits from AI, potentially exacerbating existing inequalities in science. These findings have implications for the equity and sustainability of the research enterprise, especially as the integration of AI with science continues to deepen.

摘要

人工智能(AI)的迅速发展有望重塑几乎每一个工作领域。尽管人们为理解AI的经济影响付出了巨大努力,但我们仍缺乏对使用AI给科学研究带来的益处的系统理解。在此,我们开发了一个测量框架,以估算AI在科学领域的直接使用情况及其相关益处。我们发现,AI的使用及其带来的益处似乎在整个科学界广泛存在,自2015年以来增长尤为迅速。然而,AI教育与它在研究中的应用之间存在巨大差距,凸显了AI专业知识供需之间的不匹配。我们的分析还揭示了人口统计学差异,女性或黑人科学家比例较高的学科从AI中获得的益处较少,这可能会加剧科学界现有的不平等现象。这些发现对研究事业的公平性和可持续性具有启示意义,尤其是在AI与科学的融合不断加深的情况下。

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