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A new “bottleneck pressure” measure tracks where AI could raise the value of work it cannot yet do
The paper’s author says the measure draws on 288 million U.S. job postings and GPT-4 feasibility ratings.
TLDR
The author of a new paper says AI exposure measures focus on work AI can do. Their proposed “bottleneck pressure” measure instead examines where work AI cannot yet do may become more valuable as AI speeds up other tasks. Built from 288 million U.S. job postings mapped to O*NET tasks and GPT-4 feasibility ratings, it shows how the same task can face different pressure in different occupations.
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