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METR · May 8, 2026

Task Substitution and Uplift

framework Model EvaluationAI Engineering
Why it matters

METR distinguishes three measures of AI productivity: time saved on the pre-AI task mix, value gained after people reallocate their work, and time saved on the post-AI task mix. Under stated simplifying assumptions, old-task uplift is a lower bound and new-task uplift an upper bound on value uplift, because AI changes which tasks people choose to attempt.

My takeaway: Name the uplift measure before comparing productivity claims. Track the old and new task distributions, quality-adjusted value, elapsed time, review and rework, and tasks that became feasible only with AI; publish the allocation and rationality assumptions, and avoid translating a speedup on a selected task set directly into organization-wide value.
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