Evaluating the disruption of COVID-19 on AI innovation using patent filings

M. Alexopoulos, Kelly A. Lyons, Kaushar Mahetaji, Keli Chiu
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引用次数: 1

Abstract

Economists have long recognized that technological innovation is a key contributor to economic growth due to its impact on productivity. In this paper, we explore the impact of COVID-19 on innovation in artificial intelligence (AI) to better understand future effects on economic growth and productivity. Using patents as a measure of innovation and knowledge production, we analyze monthly patent application filing data from January 2015 to June 2021 to compare and assess trends. Past research has shown that growth in patents in the fields of AI have accelerated since 2012, with 6.5 times more annual filings occurring from 2006 to 2017. Here, we focus specifically on determining if the pandemic has had an impact on this acceleration in AI-related innovation. To accomplish this task we must confront the challenge in using up-to-date patent data for this kind of analysis due to the fact that there are considerable time lags associated with patent filing dates and their ultimate publication dates. In real-time situations such as COVID-19, it is, therefore, difficult to ascertain impact using the publicly available patenting data directly. In this paper, we propose a novel approach for examining existing and up-to-date publicly available patent filing data and use that method to gain new insights into the pandemic’s effects on AI-related innovation. Our findings suggest that the pandemic has had a slowing impact on the rate of innovation in these areas but that the downturn may be reversing.
利用专利申请评估COVID-19对人工智能创新的影响
经济学家早就认识到,由于技术创新对生产率的影响,它是经济增长的关键因素。本文探讨了2019冠状病毒病对人工智能创新的影响,以更好地了解未来对经济增长和生产力的影响。我们将专利作为衡量创新和知识生产的指标,分析了2015年1月至2021年6月的每月专利申请数据,以比较和评估趋势。过去的研究表明,自2012年以来,人工智能领域的专利增长加速,2006年至2017年的年申请量增长了6.5倍。在此,我们特别侧重于确定大流行是否对人工智能相关创新的加速产生了影响。为了完成这项任务,我们必须面对使用最新专利数据进行这种分析的挑战,因为专利申请日期及其最终出版日期存在相当大的时间滞后。因此,在COVID-19等实时情况下,很难直接使用公开的专利数据来确定影响。在本文中,我们提出了一种新的方法来检查现有的和最新的公开专利申请数据,并使用该方法来获得关于大流行对人工智能相关创新影响的新见解。我们的研究结果表明,疫情对这些地区创新速度的影响正在放缓,但这种低迷可能正在逆转。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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