Effects of Artificial Intelligence on Labor Markets

人工智能对劳动力市场的影响

• 批准号: 2117095
• 负责人: Anastassia Fedyk
• 金额: $ 18.42万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2117095&HistoricalAwards=false
• 关键词: Effects; Artificial; Intelligence; Labor; Markets

To what extent are recent advances in technology replacing white collar jobs? While prior automation technologies, such as robotics, impacted menial labor in sectors such as manufacturing, emerging technologies such as artificial intelligence are meant to automate the types of tasks (prediction and decision-making) that are associated with white-collar workers and that are more prominent in service-oriented industries. This project focuses on the banking industry and uses a detailed rich dataset that includes job histories, education records, demographics, and skills. The project explores individual banks’ adoption of technology through the human capital lens, characterizing technical capabilities of each bank’s employees based on their reported skills. The project will first document stylized facts on modern technical talent, including its demographic composition and educational attainment. The research will then examine the determinants of technological investments by firms, linking technological investments to bank size, previous efficiency, and business model. Finally, the project will study the impact of banks’ technology adoption on their workforce, by considering changes in the composition of banks’ employees’ job functions and primary skill focus areas. The research will examine which job functions and skills are being displaced by technology, and which jobs appear to be complementary to technological investments. The project will have policy implications on the role of artificial intelligence investments in the labor markets. This research will study adoption of technology in service-oriented industries and the resulting impact on white collar jobs. Using detailed granular data on workers in the banking industry, the research will characterize each individual employee as either non-technical, a user of off-the-shelf tools, having basic technical skills, or having advanced technical skills. This approach will lead to a measure of bank-level investments in technology, based on the share of a given bank’s workforce that is comprised of advanced technical employees. The project will provide a detailed characterization of modern technical talent across demographics and educational attainment, and consider the determinants of technological investments by firms. Specifically, the research will study whether larger banks are more able to adopt technology, whether ex ante efficiency enhances or hinders technology adoption, and whether adoption of new technologies is more pronounced among institutions with more reliance on processing soft information. The research will further examine the impact of banks’ technology adoption on their workforce, by taking into account the changes in the composition of banks’ employees’ job functions and primary skill areas. To link changes in technology to changes in labor composition, the project will employ long-difference regressions to observe long-term effects, and distributed lead-lag models to test for pre-trends and reverse causality.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

技术的最新进步在多大程度上取代了白色领工作？虽然之前的自动化技术（如机器人技术）影响了制造业等行业的体力劳动，但人工智能等新兴技术旨在自动化与白领工人相关的任务类型（预测和决策），这些任务在服务型行业中更为突出。该项目专注于银行业，并使用详细的丰富数据集，包括工作历史，教育记录，人口统计和技能。该项目通过人力资本透镜探讨了各家银行采用技术的情况，根据每家银行雇员报告的技能来描述他们的技术能力。该项目将首先记录现代技术人才的程式化事实，包括其人口构成和教育程度。然后，研究将探讨企业技术投资的决定因素，将技术投资与银行规模、以前的效率和商业模式联系起来。最后，该项目将通过考虑银行员工工作职能和主要技能重点领域构成的变化，研究银行采用技术对其员工队伍的影响。这项研究将审查哪些工作职能和技能正在被技术取代，哪些工作似乎是技术投资的补充。该项目将对人工智能投资在劳动力市场中的作用产生政策影响。这项研究将研究服务型行业中技术的采用以及对白色领工作的影响。该研究使用银行业员工的详细粒度数据，将每个员工描述为非技术人员，现成工具的用户，具有基本技术技能或具有高级技术技能。这一方法将导致衡量银行一级的技术投资，其依据是特定银行的高级技术员工所占的比例。该项目将详细描述现代技术人才在人口统计和教育程度方面的特点，并考虑公司技术投资的决定因素。具体而言，研究将研究大型银行是否更有能力采用技术，事前效率是否会促进或阻碍技术的采用，以及在更依赖于处理软信息的机构中采用新技术是否更明显。该研究将进一步研究银行采用技术对其员工队伍的影响，同时考虑到银行员工工作职能和主要技能领域构成的变化。为了将技术变化与劳动力构成的变化联系起来，该项目将采用长差回归来观察长期影响，并采用分布式超前滞后模型来测试前趋势和反向因果关系。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。