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Back to datasetsKey Variables Task-level AI exposure scores; mean exposure; dispersion of exposure; employment effects; wage effects; firm productivity measures AI/Tech Tracking NLP-based AI and ML exposure measurement; task-level automation potential Access Details Available from authors; working paper access via NBER/SSRN Notes Uses NLP to measure dynamic exposure varying across firms and time; theoretical framework distinguishing direct/indirect productivity effects; validated against firm hiring patterns
Hampole et al. (2025)
Artificial Intelligence and the Labor Market
AI-focusedRestricted/RDCBoth
Visit Dataset- Specific Type
- AI exposure measure
- Dataset Type
- True panel/Longitudinal
- Institution
- Northwestern University; Yale University; University of Minnesota; Federal Reserve Bank of Minneapolis
- Institution Type
- Academia
- Level of Focus
- Worker-task; aggregated to firm
- Most Granular Level
- Task level within occupations
- Perspective
- Both
- Time Coverage
- 2010-2023
- Frequency
- Annual
- Sample Size
- 58 million LinkedIn profiles; comprehensive job database
- Geographic Detail
- National (US)
- Occupational Classification
- LinkedIn occupation classifications
- Industrial Classification
- LinkedIn industry classifications
- Other Classification
- Firm-level aggregations; geographic coverage
Key Papers
Hampole et al. (2025) NBER Working Paper w33509