AI's Effect on Jobs: US Commuting Zones' Evidence

Published Date: 12/08/2024

Harnessing the potential of artificial intelligence has been a major focus in recent years. But how will these advances affect labor markets and employment? A recent study explores the employment effect of AI adoption in US Commuting Zones.

Artificial intelligence (AI) has been viewed as one of the most transformative and disruptive technologies of recent times. With improvements in machine learning techniques and the growing availability of vast amounts of digital data, the last two decades have witnessed a tremendous increase in the use of AI applications.

However, a pressing policy question is how these advances will affect labor markets and especially employment. On the one hand, intelligent tools promise to enhance human capabilities and create new demand for certain skills. On the other hand, AI may surpass workers in decision-making tasks and make them redundant, or it may fuel automation.

A recent study by Bonfiglioli et al. (2023) explores the employment effect of the early phase of AI adoption, exploiting variation across US Commuting Zones (CZs) over the period 2000-2020. The study takes a broad definition of AI as algorithms applied to big data, and its diffusion started in the early 2000s and accelerated after 2010.

The study measures AI adoption across US Commuting Zones by classifying AI-related occupations as those whose job postings most frequently require software used for machine learning and data analysis. The baseline classification of AI-related occupations comprises 19 titles, such as data scientists, computer programmers, software developers, and web designers.

Between 2000 and 2020, the employment share of AI-related occupations has almost doubled in the US, rising from 0.14% to 0.20%. Most of this increase has taken place after 2010. There are sizable differences in the diffusion of AI technologies across industries. AI adoption is most prevalent in the service sector, especially in advanced branches such as information, professional, scientific and business services.

The study finds a negative effect of AI adoption on employment. CZs specialized in sectors experiencing a boom in AI-related employment had stronger rates of AI adoption, which in turn caused them to suffer a relative slowdown in employment. Quantitatively, the estimates imply that if the CZ with average AI adoption over the sample period had hypothetically had no adoption at all, its employment rate would have grown by 0.6 percentage points more.

The results are robust to controlling for several additional labor market shocks, such as import competition from China, the adoption of industrial robots, and the increased usage of ICT. They also hold when using alternative definitions of AI-related occupations and when controlling for outliers in various ways.

The study also finds that the negative effect of AI adoption is not limited to the service sector but also extends to employment in manufacturing, where the use of these technologies is still limited. Specifically, the manufacturing sector accounts for almost 45% of the overall impact of AI adoption on employment, against 60% for the service sector.

The study concludes that recent improvements in the field of AI have triggered much hype about the future of work. While nobody can predict the exact direction that new innovations and applications will take, it is important to start from understanding the consequences that these technologies have already had. The results point toward robust negative effects of AI adoption on employment for most workers and sectors.

FAQS:

Q  What is the main focus of the study?

A  The study explores the employment effect of AI adoption in US Commuting Zones.

Q  How does the study measure AI adoption?

A  The study measures AI adoption by classifying AI-related occupations as those whose job postings most frequently require software used for machine learning and data analysis.

Q  What are the main findings of the study?

A  The study finds a negative effect of AI adoption on employment, with CZs specialized in sectors experiencing a boom in AI-related employment having stronger rates of AI adoption, which in turn caused them to suffer a relative slowdown in employment.

Q  Are the results robust to controlling for other labor market shocks?

A  Yes, the results are robust to controlling for several additional labor market shocks, such as import competition from China, the adoption of industrial robots, and the increased usage of ICT.

Q  What are the implications of the study's findings?

A  The study's findings point toward robust negative effects of AI adoption on employment for most workers and sectors, highlighting the need to understand the consequences of AI adoption on labor markets and employment." "Q: What is the main focus of the study?

A: The study explores the employment effect of AI adoption in US Commuting Zones.

Q: How does the study measure AI adoption?

A: The study measures AI adoption by classifying AI-related occupations as those whose job postings most frequently require software used for machine learning and data analysis.

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