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Schwarcz AI-Powered Lawyering 2025

AI-Powered Lawyering: AI Reasoning Models, Retrieval Augmented Generation, and the Future of Legal Practice

AI-focusedPublicWorker-side
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Specific Type
Experimental AI usage evidence
Dataset Type
Cross-sectional
Institution
University of Minnesota; University of Michigan; Centre for Governance of AI
Institution Type
Academia
Level of Focus
Individual
Most Granular Level
Individual law student level
Perspective
Worker-side
Time Coverage
2025
Frequency
One-time experiment
Sample Size
127 law students
Geographic Detail
National (US)
Occupational Classification
Law students/Legal professionals
Industrial Classification
Legal services
Other Classification
Task complexity; legal specialization areas
Key Variables
Task completion time; work quality; analytical depth; hallucination rates; productivity metrics
AI/Tech Tracking
Vincent AI (RAG) and o1-preview reasoning model usage
Access Details
Available from authors
Notes
Vincent AI: 38-115% productivity gains; o1-preview: 34-140% gains; both tools enhanced legal work quality