Mercor, Stanford, NBER Release TaskNet: 79 Missing Tasks Worth ~$140B a Year
soumitrashukla9 · x · 2026-10-28
Researchers from Stanford, Mercor, the ONET Resource Center, and NBER released TaskNet, an open-source task catalog built on the US Department of Labor's ONET taxonomy but updated for how AI is changing work.
- Problem: ONET updates lag behind reality — workers take on new tasks before job descriptions catch up, and economists use ONET to estimate which jobs AI will transform. Incomplete lists mean incomplete estimates.
- Method: TaskNet interviews workers directly with a fast, scalable interviewer, also eliciting judgments on automation-relevant task features like how easy it is to judge output quality or define success a priori.
- Findings: Across 6 occupations, TaskNet identified 79 validated tasks with no ONET counterpart, including 5 created or reshaped by AI adoption. Mercor estimates the missing work represents roughly $140B a year in wages.
- Implication: TaskNet provides infrastructure to keep occupational task data current as AI reshapes professional work.
Related event: Stanford and Mercor Launch TaskNet to Map AI's Impact on Jobs(8 posts)→
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