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AI/Robotics, Labor Markets and Demography

Paper Session

Saturday, Jan. 4, 2020 2:30 PM - 4:30 PM (PDT)

Marriott Marquis, Grand Ballroom 10
Hosted By: American Economic Association
  • Chair: Karen N. Eggleston, Stanford University and NBER

Automation Versus Procreation, aka Bots Versus Tots

Hal R. Varian
,
Google

Abstract

Several recent papers have considered the impact of automation on labor demand in the coming decades. But demand is only one side of the labor market: the supply of labor will also change dramatically in the next 50 years. The net outcome on wages and employment will depend on the relative magnitude of these shifts in demand and supply. I conclude that the expected demographic changes are of similar magnitude to forecasts of demand changes due to automation at least in the next 20 years.

The analysis first discusses a simple model of the labor market, and the changing relationship between jobs and tasks, including which tasks --- and which jobs --- will be automated and the role of education and training. Subsequent sections discuss productivity and the demographics of the US labor market, including historical trends in fertility and civilian labor force; how in other OECD countries workforce aging is correlated with heavy investments in automation/robotics; and the importance of analyzing both supply and demand of labor. Focusing on the demand side alone is misleading from a policy perspective.

Most jobs, even low level jobs, consist of a variety of tasks that are difficult to automate, so we can expect them to be with us for a long time. The demographic shifts, on the other hand, are hitting us in the near term future, and it is likely that we will see a tight labor market for decades to come. Increasing productivity, most likely with automation, will become increasingly important.

The Impact of Robots on Staffing in Nursing Homes

Toshiaki Iizuka
,
University of Tokyo
Yong Suk Lee
,
Stanford University
Karen N. Eggleston
,
Stanford University and NBER

Abstract

Robots are increasingly being adopted to remedy the challenges posed by rapidly aging demographics in many countries. Japan, in particular, has been actively developing and deploying robots in nursing homes to deal with labor shortages and high turnover rates among caregivers. Moreover, Japan has been introducing subsidies that help nursing homes purchase robots. In this project, we examine how robots affect staffing and wages in nursing homes using establishment-level 2017 micro-data from Japan. The empirical identification strategy utilizes variation in robot subsidies across prefectures, as well as self-reported attitudes toward adopting robots (lack of knowledge, inappropriate, or concerns about malfunction) as instrumental variables. We do not find strong evidence that robots significantly impact staffing at nursing homes, although there is some evidence that robots reduce separation rates of caregivers and positively impact wages, suggesting upskilling of care givers as robots assist with burdensome tasks (e.g., nighttime monitoring, back pain from transferring elderly in and out of bed). These results may indicate that robots complement lower-skilled workers in the service sector in tight labor markets, but the evidence is not robust across specifications.

How Would AI Regulation Change Firms’ Behavior? Evidence from Thousands of Managers

Yong Suk Lee
,
Stanford University
Benjamin Larsen
,
Copenhagen Business School
Michael Webb
,
Stanford University
Mariano-Florentino Cuéllar
,
California Supreme Court and Stanford University

Abstract

We examine the impacts of different proposed AI regulations on managers’ intentions to adopt AI technologies and on their AI-related business strategies. We conduct a randomized online survey experiment on more than a thousand managers in the U.S. We randomly present managers with different proposed AI regulations, and ask them to make decisions about AI adoption, budget allocation, hiring, and other issues. We have four main findings: (1) information about AI regulation generally reduces the rate of adoption of AI technologies. Nonetheless, industry- and agency-specific AI regulation has a smaller impact than general AI regulation. (2) Information about regulation induces firms to think. That is, firms spend more on developing AI strategy and hire more managers. This is at the cost of hiring other workers and training current employees. (3) The impact of information about AI regulation on innovation differs by industry and firm size. AI regulation increases intent to file patents in the healthcare and pharmaceutical sectors, but reduces it in the retail sector. Moreover, AI regulation information reduces AI adoption in small firms and is more likely to reduce their innovative activity. (4) Information about AI regulation increases firms’ perceptions of the importance of safety and transparency issues related to AI.
Discussant(s)
Ramin Toloui
,
Stanford University
Robert Seamans
,
New York University
Kristina McElheran
,
University of Toronto
JEL Classifications
  • O3 - Innovation; Research and Development; Technological Change; Intellectual Property Rights
  • J2 - Demand and Supply of Labor