AI Exposure Scores: what they measure, what they miss, and what comes next
Why AI job-impact scores miss what policymakers actually need to know
A widely-cited 2023 study measured how much AI could assist with different jobs, but researchers now show these scores oversimplify the real world—ignoring when and where jobs actually change, who gets hurt or helped, and whether workers can actually use AI tools. The gap widens because policymakers keep citing the original scores without knowing their limitations, leaving policy decisions built on incomplete evidence.
Governments and companies are making decisions about worker retraining, hiring, and regulation based on these exposure scores. If the scores ignore timing, geography, and actual adoption patterns, policymakers might protect the wrong workers or miss those most at risk. The authors argue the real fix requires researchers and policymakers to talk directly—sharing better data, involving workers in the research itself, and shifting from predicting job losses to actively preparing for them.