News & Media
Press coverage, op-eds, and external citations of RISEI Lab research
Featured Coverage
FT feature engaging with the Yin, Vu & Persico finding that AI occupational exposure scores diverge widely across frontier models. Full article behind paywall.
WSJ report on the NBER working paper showing AI occupational exposure scores diverge 3.6× across models. WSJ Tech · Coverage of AI exposure findings and the divergence across frontier models.
CEPR / VoxEU policy column by Yin, Vu, and Persico extending the findings of the NBER paper on LLM occupational exposure instability into a policy recommendation. VoxEU policy column by Yin, Vu & Persico (2026).
Who Uses AI? Platform Selection and the Measurement of Occupational AI Exposure
Yin & Ogut (2026), arXiv:2605.21743. Platform-derived AI exposure scores conflate task applicability with the occupational composition of platform users. Changing only the platform input shifts the post-ChatGPT employment coefficient by a factor of 1.9. Workforce reweighting attenuates estimates 42 to 93 percent.
Automation and Disability: How Functional Limitations Shape Vulnerability
Vu & Yin (2026). Aggregate disability vs. non-disability robot-exposure effects are indistinguishable. Sensory impairments bear 50 percent larger employment losses while cognitive limitations show none.
How (un)Stable Are LLM Occupational Exposure Scores? Yin, Vu, & Persico (2026). NBER WP #35110.
Yin & Guerrero (2026). Published article in Rehabilitation Counseling Bulletin. DOI: 10.1177/00343552261442986
Yin, Seo & Vu (2026). First national 15-state analysis of Section 14(c) elimination. No aggregate job loss, −12.4% welfare dependence.
Coverage of the U.S. Department of Education award funding the Maine Pathways to Partnerships model project on transition services and competitive integrated employment for youth with disabilities.
AIR expert Q&A on AI and the future of work, disability employment, workforce development, and how automation, artificial intelligence, and broadband access reshape labor market opportunities.
Op-Eds & Commentary
Policy column by Yin, Vu & Persico. The share of U.S. occupations classified as high direct exposure to AI ranges from 2.7% to 51.5% on identical task data, depending on which frontier model is used to score them.
Congress Blog op-ed on the earnings gap between workers with and without disabilities and the aggregate economic cost of unequal pay.
Commentary on the labor market and consumer market case for disability inclusion, drawing on the Hidden Market and Uneven Playing Field series.
Yin, L. M. (2019), pages 43–48. Business case for disability inclusion in hiring, procurement, and consumer strategy.
Opinion piece by Yin & Schneider on graduation rates, student outcomes, and accountability at community colleges.
Earlier Press
The One Size Does Not Fit All report (Yin & Shaewitz, 2016) was featured on The Wall Street Journal's Real Time Economics blog. Dr. Yin has also delivered Capitol Hill briefings including Closing the Pay Gap for Workers with Disabilities (2015, Cannon House Office Building) and Research to Inform Policy with the Interagency Committee on Disability Research (2015). Additional coverage is added here as it is published.