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A survey of 349 technical workers shows they self-report a 1.4 to 2 times increase in work value due to AI tools, with a median speed increase of 3 times. Respondents also project further gains, estimating a 2.5 times value increase by March 2027, but results may be overstated, particularly among METR staff.
We reviewed the “Risks from automated R&D” section of Anthropic’s February 2026 Risk Report , producing two corresponding review documents: our original review and our updated review . We recommend that readers refer to our original review, which represents our review of the report as originally received. We expect the public version of the report to be updated to resemble the changes anticipated in our updated review in content, though not necessarily in exact wording. We expect our updated review to cover those changes, but if the updated public version includes any changes that materially affect our opinion...
Summary: We describe three different definitions of the productivity impact of AI (AKA uplift), and show there’s reason to expect: \[\text{uplift on old tasks} \leq \text{uplift in value} \leq \text{uplift on new tasks}\] Three Measures of Uplift One complication in measuring AI’s effect on productivity is that it has different effects on different tasks, and this causes people to change how they allocate their time between tasks. This makes it more difficult to talk about the effect of AI on overall productivity. We use “old tasks” to mean the set of tasks you’d do in a typical day before AI is available – yo...