Ai, Labor, Productivity and the Need for Firm-Level Data
Ai, Labor, Productivity and the Need for Firm-Level Data
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DOI：
10.3386/w24239
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发表时间：
2018-01
期刊：
影响因子：
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通讯作者：
Robert C. Seamans;Manav Raj
中科院分区：
文献类型：
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作者：
Robert C. Seamans;Manav Raj
我们总结了现有的关于机器人和人工智能的采用及其对劳动力和生产率的影响的实证研究结果，并主张在企业层面更系统地收集这些技术的使用情况。现有的实证研究主要使用按行业或国家汇总的统计数据，这排除了对机器人和人工智能补充或替代劳动力的条件进行深入研究。此外，公司一级的数据还可用于研究对不同规模公司的影响、市场结构在技术采用中的作用、对企业家和创新者的影响以及对区域经济的影响等。我们强调了几种方法，这种企业层面的数据可以收集和使用的学者，政策制定者和其他研究人员。
We summarize existing empirical findings regarding the adoption of robotics and AI and its effects on aggregated labor and productivity, and argue for more systematic collection of the use of these technologies at the firm level. Existing empirical work primarily uses statistics aggregated by industry or country, which precludes in-depth studies regarding the conditions under which robotics and AI complement or are substituting for labor. Further, firm-level data would also allow for studies of effects on firms of different sizes, the role of market structure in technology adoption, the impact on entrepreneurs and innovators, and the effect on regional economies amongst others. We highlight several ways that such firm-level data could be collected and used by academics, policymakers and other researchers.