New paper builds "bottleneck pressure" metric from 288M job postings to value work AI can't do
soumitrashukla9 · x · 2026-10-22
A new paper, "Technology Bottlenecks," flips AI-exposure measurement: instead of asking what AI can do, it estimates where the marginal value of work AI cannot yet do rises as AI speeds up the rest of a job.
- Maps 288 million US job postings line by line to ONET tasks
- Combines GPT-4 feasibility ratings from Eloundou et al. (2024)
- Derives a task-level "bottleneck pressure" measure: for AI-infeasible tasks, pressure is a function of the exposure of the other tasks in the occupation
The metric helps identify which human-only tasks may gain value as AI adoption spreads.
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