This project measures the impact of AI on workers and employers in California.
Background
Artificial Intelligence (AI) technology has rapidly advanced over the past two decades, most recently with the widespread diffusion of generative AI tools that began in late 2022. As AI technology becomes better at performing tasks currently being done by workers, its adoption by employers means some workers are being displaced. On the other hand, as these technologies are more widely adopted, some workers may benefit if AI makes them more productive.
Despite growing concern, empirical evidence on the impact of AI on labor market outcomes is limited and many foundational questions remain about the extent of AI-induced displacement of jobs. For example, are workers in certain occupations, industries or from specific demographic groups more likely to be displaced? Are their experiences different from other types of displacement, including automation and earlier precursors to AI?
As the world’s fifth largest economy, California is an ideal state to study AI’s impact due to its size, data, and proximity to AI innovations.
Research Project
The goal of this project is to better understand earnings and employment outcomes for workers in industries that are adopting AI technologies. First and foremost, the project studies how AI is reshaping the labor market — both for workers and for employers. On the worker side, we track whether AI-impacted workers are hired, laid off, switching jobs, or staying put, and how these changes affect their earnings and employment. We will measure whether AI-displaced workers are able to find new jobs with comparable earnings. On the employer side, the project will use job posting data to consider how demand for AI skills is changing, which firms are embracing AI, whether AI-intensive companies are growing, what types of workers they are hiring, and whether the skills jobseekers are pursuing align with what employers want.
To estimate the effect of job loss on earnings and employment for AI-impacted workers, we will compare outcomes for unemployment insurance claimants from high AI exposure occupations to outcomes for similar claimants from low exposure occupations. We will also estimate the probability of these workers being re-employed in an AI-intensive company.
Research Team
Dr. Benjamin Hyman (Co-Principal Investigator), Professor Till von Wachter (Co-Principal Investigator), Dr. Roozbeh Moghadam and Dr. Swapnil Motghare
Results
Forthcoming