CONCEPT
The Task-Based Framework
Autor's analytical architecture that decomposes jobs into discrete tasks, each scored by its susceptibility to automation — the framework that reveals why AI reshapes rather than eliminates occupations.
The task-based framework is David Autor's signature analytical contribution to labor economics. Rather than treating jobs as indivisible units that either survive or disappear under technological change, the framework decomposes every occupation into a bundle of discrete tasks — some routine, some non-routine; some cognitive, some manual; some interpersonal, some analytical. Technology enters this bundle selectively, automating some tasks while leaving others untouched, and in doing so transforms the occupation without eliminating it. The framework's empirical power lies in its predictive precision: by measuring the task composition of an occupation and the automation susceptibility of each task, one can forecast with unusual accuracy which jobs will be hollowed out, which will expand, and which will fundamentally change in character. Applied to AI, the framework predicts a reorganization rather than a collapse of the labor market.
In The You On AI Field Guide
The framework emerged in the early 2000s from Autor's collaboration with Frank Levy and Richard Murnane, whose 2003 paper 'The Skill