NBER: PhDs who wrote with AI less likely to stay in academia

A National Bureau of Economic Research working paper finds that roughly 30% of US STEM PhD dissertations filed in the first five months of 2026 contain AI-generated text in their abstracts, and the graduates who wrote with AI are measurably less likely to continue in academia. Nature reported the finding this week.

NBER paper 35859, by economist Daniel P. Gross with co-authors Dror Shvadron and Hansen Zhang, examined more than 226,000 STEM dissertations completed between January 2019 and May 2026 at US universities, flagging abstracts via the Pangram AI-detection service. Prevalence climbed from 1.7% in 2023 to 18.8% in 2025 before reaching 29.4% in early 2026. Mathematical and computer sciences led at 36%, engineering at 35%, and physical sciences trailed at 22%. 41% of dissertations by graduates from non-English-speaking countries contained AI-generated abstracts, against 23% from English-speaking countries.

The career finding is the sharper one. Among US-origin graduates with AI-written abstracts, PhDs were 17% less likely to pursue academic employment and 16% more likely to work in industry than peers without flagged AI use.

Researcher Ang Liu told Nature that AI drafting works best where prior knowledge is substantial, and that in genuinely unexplored territory "rigorous research training becomes even more important."

NBER Working Paper 35859 remains unreviewed.