AI Diffusion & Labour
Adoption measurement, task-level exposure, productivity studies and what the evidence does and does not show.
6concepts
65flashcards
44minutes of reading
- 01 Adoption Patterns and What Usage Data Shows What measured usage reveals about where these systems are actually applied, the augmentation-automation split, and why usage concentration differs from exposure predictions.
- 02 Task Exposure Versus Job Replacement Why the unit of analysis is the task rather than the occupation, what exposure measures and what it does not, and the two opposing forces that determine whether exposure becomes displacement.
- 03 General-Purpose Technologies and the Productivity J-Curve Why technologies that eventually transform an economy first depress measured productivity, how unmeasured intangible investment produces a J-shaped path in the statistics, and why the theory is hard to test while you are standing in the dip.
- 04 Measuring Diffusion Honestly Why most claims about AI's economic impact rest on evidence that cannot support them, the hierarchy of evidence quality, and the specific questions to ask of any figure.
- 05 Skill Distribution and Who Benefits The consistent finding that gains concentrate among lower-skilled workers, the competing explanations for it, and the conditions under which the pattern reverses.
- 06 What the Productivity Studies Actually Found The controlled experiments measuring AI's effect on work output, why their results range from large gains to measured slowdowns, and what distinguishes the settings.