New Approach to Measuring AI’s Impact on Employment
As artificial intelligence continues to disrupt industries worldwide, a team of researchers at Northeastern University is developing a groundbreaking model that evaluates the real risk of job loss due to AI. Unlike traditional methods that rely heavily on unemployment statistics, this model focuses on how AI redefines job roles by altering the skills and tasks associated with them.
“We need to understand that the impact of AI on the job market is not just at the end of a job when you get displaced,” said Esteban Moro, a professor of physics at Northeastern and a member of the university’s Network Science Institute. “You can get your job skills or job tasks redefined. You can move to a different job within the same company, or even remain in the same role but perform tasks differently and more efficiently.”
Beyond Traditional Employment Data
Moro emphasizes the limitations of existing labor data to capture the evolving nature of work. He highlights the need to analyze how the core skills within jobs are changing. “All of our industries are affected by AI, but within the aggregated data we’re using now, I think we are missing most of the changes,” he explained.
To address this gap, Moro and a team of collaborators from the University of Pittsburgh and Indiana University have created a skill-based framework. Their model assesses the likelihood of workers being replaced by AI, based not just on job titles but on the specific skill sets required for those jobs.
“We’re not just looking at whether a job disappears,” Moro said. “We’re analyzing how the tasks and skills within that job are transformed, which is a much more nuanced approach.”
Debunking Dire Predictions
Historically, many models have predicted that up to 50% of U.S. jobs could be at risk due to AI, with some suggesting that 40% of certain job types might vanish entirely. However, research by Moro and his colleagues, published in the journal PNAS Nexus, suggests that these doomsday forecasts have not materialized.
“What we found in this paper is that none of those doomsday predictions were accurate. They didn’t happen,” Moro stated.
He pointed to radiology as a key example. While early AI applications in medical imaging sparked fears of widespread job losses among radiologists, the opposite has occurred. “The number of radiologists in this country increased in the last 10 years,” Moro said. “Reading X-rays was automated, but the actual job of a radiologist involves much more than that single task.”
Understanding ‘Unemployment Risk’
The new model allows researchers to calculate what they call “unemployment risk” — a measurement that reflects how susceptible someone’s current skill set is to automation. The more automatable your skill set, the higher your unemployment risk.
“That doesn’t mean you’re going to be displaced,” Moro clarified. “People can adapt, pivot to new roles, or be upskilled by employers and educational institutions.”
This skill-based perspective provides a more adaptable and realistic understanding of how AI is affecting the workforce. It also opens up new avenues for targeted job training and workforce development policies.
The Observatory of U.S. Job Disruption
To further this research, Moro and partners at institutions like Carnegie Mellon University and MIT are working on the Observatory of U.S. Job Disruption. This initiative aims to collect vast amounts of data on job skills from resumes, job postings, and descriptions to refine their unemployment risk model.
“We have to go farther and farther, which means more data, more analysis, and more resources,” Moro said. “The only way to understand and act on what is happening is to measure it properly.”
The long-term vision includes creating a public-facing web tool where individuals can input their job title, industry, and location to receive a personalized unemployment risk score. This could be a valuable resource for workers, employers, and policymakers alike.
A Shift in Perspective
Moro’s work encourages a shift in how we think about employment and job security in the age of AI. Rather than fearing job elimination, his model highlights the importance of continuous skill development and adaptability.
“AI isn’t just taking jobs away — it’s changing how we do them,” Moro said. “If we understand those changes, we can better prepare our workforce for the future.”
This article is inspired by content from Original Source. It has been rephrased for originality. Images are credited to the original source.