Legal AI is poised to transform the work of legal professionals, and judges are no exception. This study reports on a randomized field experiment conducted in partnership with Pakistan’s Federal Judicial Academy, in which AI technology and skills were integrated into the workflow of Pakistan judges. Our team developed an LLM-based AI support tool designed to assist judges in their work, including a RAG system facilitating search, citation, and summarization of Pakistani legal precedents.
About one-third of Pakistan’s trial court judges (N ≈ 764) signed up for the study and were randomized into two waves (March and September 2024), where they received access to this AI tool along with a nine-hour training course in its capacities and limitations. We demonstrate high and persistent takeup of the tool. We then evaluate the effects of AI tools and training on judge work satisfaction, case disposal rates, and the quality of written judgments. These results provide insights into the potential of generative AI to enhance judicial efficiency and state capacities globally.
Bio: Elliott Ash is an associate professor at ETH, Zurich and currently a scholar in residence at New York University Law School. Ash is a scientific lead (Human-AI Alignment Horizontal) in the Swiss AI Initiative, CEPR research affiliate (Political Economy), associate editor at Economic Journal, and recipient of a European Research Council Starting Grant. Ash has held previous research appointments at University of Warwick (assistant professor) and Princeton University (postdoc). He earned a Ph.D. in economics and J.D. from Columbia University, a B.A. (Plan II Honors) from University of Texas at Austin, and an LL.M. in international criminal law from University of Amsterdam.
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