Analysing historical patterns of artificial intelligence (AI) adoption can inform decisions about AI capability uplift, but research to date has provided a limited view of AI adoption across various fields of research. In this study we examine worldwide adoption of AI technology within 333 fields of research during 1960-2021. We do this by using bibliometric analysis with 137 million peer-reviewed publications captured in The Lens database. We define AI using a list of 214 phrases developed by expert working groups at the Organisation for Economic Cooperation and Development (OECD). We found that 3.1 million of the 137 million peer-reviewed research publications during the entire period were AI-related, with a surge in AI adoption across practically all research fields (physical science, natural science, life science, social science and the arts and humanities) in recent years. The diffusion of AI beyond computer science was early, rapid and widespread. In 1960 14% of 333 research fields were related to AI (many in computer science), but this increased to cover over half of all research fields by 1972, over 80% by 1986 and over 98% in current times. We note AI has experienced boom-bust cycles historically: the AI "springs" and "winters". We conclude that the context of the current surge appears different, and that interdisciplinary AI application is likely to be sustained.

翻译：分析人工智能采纳的历史模式可为人工智能能力提升决策提供参考，但现有研究对人工智能在各研究领域的发展状况认识有限。本研究通过文献计量方法，利用Lens数据库中收录的1.37亿篇同行评审出版物，考察1960-2021年间全球333个研究领域对人工智能技术的采纳情况。我们采用经济合作与发展组织（OECD）专家工作组制定的214个人工智能相关短语列表来界定人工智能。研究发现，在此期间1.37亿篇同行评审研究出版物中，有310万篇与人工智能相关，且近年来人工智能采纳几乎全面覆盖所有研究领域（物理科学、自然科学、生命科学、社会科学、艺术与人文学科）。人工智能向计算机科学以外的领域扩散具有早期性、快速性和广泛性特征：1960年333个研究领域中有14%（主要为计算机科学领域）涉及人工智能，但至1972年这一比例已扩展至全部研究领域的一半以上，1986年超过80%，而当前则已达到98%以上。我们注意到人工智能在历史上经历了兴衰周期：所谓的"人工智能之春"与"人工智能之冬"。研究结论表明，当前人工智能浪潮的宏观背景存在显著差异，跨学科人工智能应用可能具有可持续性。