The AI Canaries in the Job Market

A new working paper from Stanford's Digital Economy Lab: Erik Brynjolfsson, Bharat Chandar, Ruyu Chen, Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence, August 2025.

Abstract: This paper examines changes in the labor market for occupations exposed to generative artificial intelligence using high-frequency administrative data from the largest payroll software provider in the United States. We present six facts that characterize these shifts. We find that since the widespread adoption of generative AI, early-career workers (ages 22-25) in the most AI-exposed occupations have experienced a 13 percent relative decline in employment even after controlling for firm-level shocks. In contrast, employment for workers in less exposed fields and more experienced workers in the same occupations has remained stable or continued to grow. We also find that adjustments occur primarily through employment rather than compensation. Furthermore, employment declines are concentrated in occupations where AI is more likely to automate, rather than augment, human labor. Our results are robust to alternative explanations, such as excluding technology-related firms and excluding occupations amenable to remote work. These six facts provide early, large-scale evidence consistent with the hypothesis that the AI revolution is beginning to have a significant and disproportionate impact on entry-level workers in the American labor market.

Tyler Cowen has a link to a tweet stream by Bharat Chandar (one of the authors).

Here's the opening of an article from Hollis Robbins, The Canary in the Classroom:

As all the headlines shout today, a new Stanford study shows that AI is behind the struggles of young people to find jobs. “Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence,” by Erik Brynjolfsson, Bharat Chandar, and Ruyu Chen, draws on payroll data from ADP covering millions of workers across tens of thousands of firms to argue that “early-career workers (ages 22-25) in the most AI-exposed occupations have experienced a 13 percent relative decline in employment even after controlling for firm-level shocks.” In contrast, employment for more experienced workers in the same occupations (software developers, customer service representatives) has remained stable or continued to grow, as has employment in less AI-exposed fields like nursing.

The study and the media want to see this as a story of AI displacement. I think it is more complicated and yes, higher education practices are partially to blame.

The study dates this stagnation to 2022, which caught my eye from the higher ed perspective. These are young people disrupted by the pandemic whose lives and experiences are more online than any other. I recall in May 2022 teaching a half dozen college seniors how to shake hands when walking into a job interview (firmly, for two and a half shakes), alarmed that the online platform, Handshake, did not teach this skill. It isn’t really a dean’s job, but somebody had to do it, and better late than never, just before the diploma.

The Stanford study also differentiates between jobs that AI “automates” but not “augments,” noting that jobs for people who use ChatGPT or Claude are still growing. This is interesting; more below.

But broadly, the Stanford study finds the 22-25 year old group is vulnerable across sectors. They conclude that “early, large-scale evidence consistent with the hypothesis that the AI revolution is beginning to have a significant and disproportionate impact on entry-level workers in the American labor market” (1).

Maybe. While I see a solid quantitative analysis of who is being affected by AI, I don’t see enough focus on the how or why. The paper makes no mention of the rise of online learning, automated hiring platforms, and AI-driven recruitment tools. This seems to me a significant oversight.