New study challenges AI job displacement predictions with emphasis on job transition, not elimination

Northeastern University researcher Esteban Moro has developed a new skill-based model for measuring individual workers’ risk of job displacement due to artificial intelligence. The approach challenges traditional unemployment statistics by recognizing that AI transforms jobs by redefining skills and tasks rather than simply eliminating positions, offering a more nuanced understanding of how automation affects the workforce.

What you should know: Moro’s research reveals that existing “doomsday predictions” about AI-driven job losses have proven inaccurate when compared against real unemployment data.

• A recent study published in PNAS Nexus found that historical models predicting nearly 40% of certain jobs would disappear and 50% of all U.S. jobs would be at risk from AI did not materialize.
• The number of radiologists actually increased over the last decade despite AI automation of X-ray analysis, demonstrating how jobs evolve rather than vanish.

How it works: The new model treats each job as a collection of skills to calculate an individual’s “unemployment risk” based on how many of their skills could be automated.

• Workers with more automatable skills face higher unemployment risk, but this doesn’t guarantee displacement.
• The model accounts for workers’ ability to adapt, pivot to new roles, or receive training in new skills from companies and universities.

The big picture: Moro argues that current data collection methods miss most AI-driven workplace changes because they focus on job elimination rather than job transformation.

• “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,” Moro explains. “You can get your job skills or job tasks redefined. You can get a totally different job.”
• “All of our industries are affected by AI, but within the aggregated data that we’re using right now, I think we are missing most of the changes.”

What’s next: Moro and researchers at Carnegie Mellon University and MIT are building the Observatory of US Job Disruption to collect comprehensive data on job skills from resumes, job descriptions, and postings.

• The goal is to create a website where individuals can input their job, sector, and location to determine their personalized unemployment risk.
• “The only way to understand and act on what is happening is to measure it properly,” Moro says.