August 11, 2025
As artifical intellegence (AI) continues to seep into our day-to-day lives, a question that many often find themselves wondering is how this new technology will affect their careers. School of Computing and Information (SCI) Assistant Professor Morgan Frank is collaborating with Carnegie Mellon University’s Block Center for Technology and Society, Massachusetts Institute of Technology (MIT) FutureTech, University of Virginia, the California Policy Lab, and the U.S. Chamber of Commerce Foundation to create a wide-ranging research effort focused on understanding AI’s labor implications using high-resolution data.
“With this data, we’re going to be able to cut through the hype and get down to some empirics that can inform the conversation and help us move forward,” said Frank.
One of the ways in which this research was catalyzed was a recognized need for accurate and nuanced data surrounding job markets in recent years. The current standard for unemployment statistics is overly broad, often reporting only ‘total unemployment’ as a single figure. Data that breaks down which specific geographic regions, industries, or roles within companies are most affected is far less available, despite being an important factor in answering the questions people are asking about how AI will impact their field.
On a search to find data of this kind, Frank reached out to leading economists – including Nobel Prize winner Daron Acemoglu from MIT – to ask if it existed. In a 2019 email exchange, one explanation stuck with him: if someone is unemployed, then, by definition, they don’t have an occupation.
This fatal flaw in employment statistics is one that keeps relevant information about current job market trends obscured, making it difficult to see how developments in technology are affecting specific regions and positions within organizations. So, by reaching out to state unemployment insurance programs – who do ask what unemployed people were doing before – they aim to collect specific data that can take away these blind spots.
“This project will significantly advance our ability to quantify AI's impact on job loss,” Frank explains, “For example, we could compare trends in unemployment risk for computer and mathematics occupations in Allegheny County to major investments in AI in Pittsburgh.”
Funded by a $1.6 million grant from the Alfred P. Sloan Foundation, the goal of this research is to build a large-scale, integrated data source that serves as a reliable hub for unemployment information. It’s the first step in uncovering what’s happening beneath the surface of the U.S. labor market, while also serving as a consistent source of supporting data for potential policy change. This research is integral to shaping a more ethical and forward-looking approach to tech integration.
Find more information here. Congratulations to Morgan Frank on his involvement in this research collaboration!