Answers are grounded in this paper and cite their sources.
Computational mapping study demonstrates high-accuracy assignment of human abilities across 18,796 occupational tasks, highlighting automated frameworks for evaluating workforce exposure to AI.
A task-level mapping from 18,796 O*NET work tasks, spanning all 23 SOC major groups, to the 52 O*NET human abilities each task requires, with a graded importance weight per (task, ability) pair. The dataset contains 95,330 task-to-ability mappings. Labels were generated with a large language model against the O*NET taxonomy using one consistent method across all groups, then validated: three independent annotators each re-reviewed a 200-task audit sample and endorsed 98.9% of the model-proposed abilities. Built as the empirical foundation for the ATES (Agentic Task Exposure Score) framework, it also stands alone for research on skill demand, automation exposure, and the division of tasks between people and AI.
No takes yet. Share an insight, caveat, or question.
Gupta et al. (2026) studied this question.
Synapse has enriched 8 closely related papers on similar clinical questions. Consider them for comparative context: