Jonathan Choi (USC; Google Scholar), Amy B. Monahan (Minnesota; Google Scholar) & Daniel Schwarcz (Minnesota; Google Scholar), Lawyering in the Age of Artificial Intelligence, 109 Minn. L. Rev. 147 (2024):

We conducted the first randomized controlled trial to study the effect of AI assistance on human legal analysis. We randomly assigned law school students to complete realistic legal tasks either with or without the assistance of GPT-4, tracking how long the students took on each task and blind-grading the results.

We found that access to GPT-4 only slightly and inconsistently improved the quality of participants’ legal analysis but induced large and consistent increases in speed. AI assistance improved the quality of output unevenly—where it was useful at all, the lowest-skilled participants saw the largest improvements. On the other hand, AI assistance saved participants roughly the same amount of time regardless of their baseline speed. In followup surveys, participants reported increased satisfaction from using AI to complete legal tasks and correctly guessed the tasks for which GPT-4 was most helpful. 

These results have important descriptive and normative implications for the future of lawyering. Descriptively, they suggest that AI assistance can significantly improve productivity and satisfaction, and that it can be selectively employed by lawyers in areas where AI is most useful. Because AI tools have an equalizing effect on performance, they may also promote equality in a famously unequal profession. Normatively, our findings suggest that law schools, lawyers, judges, and clients should thoughtfully embrace AI tools and plan for a future in which they will become widespread.

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