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Back to datasetsKey Variables Work activity classifications, task success rates, scope of impact, user satisfaction (thumbs up/down), AI applicability scores AI/Tech Tracking Direct AI usage for work activities, task completion rates, automation vs augmentation patterns Access Details Available from authors upon request Notes Uses LLM-based classification; measures task success and scope; focuses on occupational implications
Microsoft Copilot Study
Working with AI: Measuring the Occupational Implications of Generative AI (Microsoft Bing Copilot Conversation Data)
AI-focusedResearch partnershipsWorker-side
Visit Dataset- Specific Type
- AI usage "In the wild"
- Dataset Type
- Cross-sectional
- Institution
- Microsoft Research
- Institution Type
- Industry
- Level of Focus
- Individual conversations mapped to work activities
- Most Granular Level
- O*NET Intermediate Work Activity (IWA) level
- Perspective
- Worker-side
- Time Coverage
- 2024
- Frequency
- One-time study
- Sample Size
- 200K anonymized conversations
- Geographic Detail
- National (US)
- Occupational Classification
- O*NET-SOC (via IWA mapping)
- Industrial Classification
- Not specified
- Other Classification
- O*NET Intermediate Work Activities (IWAs), General Work Activities (GWAs)
Key Papers
Tomlinson et al. (2025) - "Working with AI: Measuring the Occupational Implications of Generative AI"