New paper: 'bottleneck pressure' measures where work AI can't do gains value, using 288M job postings
soumitrashukla9 · x · 2026-10-23
Researchers released a new paper, "Technology Bottlenecks: Measuring Where AI Could Raise the Value of Work It Cannot Yet Do." Unlike standard AI exposure measures, it asks where the marginal value of AI-infeasible tasks rises as AI speeds up the rest of a job.
Method:
- Maps 288 million U.S. job postings line by line to their closest ONET tasks
- Combines GPT-4 feasibility ratings from Eloundou et al. (2024)
- Derives a task-level "bottleneck pressure" measure within a simple task-based framework
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