trailRoughly 19 percent of US workers could have at least half of their tasks impacted by LLMs.
Exposure ratings of O*NET occupational tasks by human annotators and GPT-4 reliably estimate which work tasks LLMs could affect
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Independently constructed AI occupational exposure indices broadly agree on which occupations are most exposed
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Headline estimates of LLM exposure at the half-of-tasks threshold include exposure via software and tooling built on LLMs, not LLM access alone
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assumed
Task-based analysis of occupational databases can meaningfully estimate occupations' exposure to AI automation
assumed
LLM task exposure measures technical potential, not realized labor-market impact or job displacement
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Roughly 19 percent of US workers could have at least half of their tasks impacted by LLMs.
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