Episode Details

Law professor Julian Nyarko has drawn attention for his studies using large language models to investigate and improve legal education and explore AI’s biases. He hopes AI can become a reliable, always-on legal learning and assistance tool to lower costs and expand access to legal services. In one recent study, he asked a group of law professors to evaluate written answers to student questions. Three-quarters of the time, the professors preferred AI-generated answers to those of their human colleagues. “AI is good at law,” Nyarko says, the challenge now is to use it most effectively, he tells host Russ Altman in this episode of Stanford Engineering’s The Future of Everything podcast.

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Episode Reference Links:

• Stanford Profile:Julian Nyarko

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Julian Nyarko, a professor of law at Stanford University.

(00:02:31) Path into AI and Law

How Nyarko’s early work led him to legal AI.

(00:05:03) Law, Economics, and Computation

How Nyarko’s training, methods, and self-taught coding shaped his research.

(00:07:23) Building the LIFT Lab

Why a law professor started a lab.

(00:09:06) Evaluating Legal AI

How AI raises fundamental questions about what counts as good lawyering.

(00:10:22) Improving Legal Services

Using AI to work faster, reduce errors, and make informed decisions.

(00:10:57) Rethinking Legal Education

How AI may change the way future lawyers learn 

(00:11:51) AI in Office Hours

How AI answers law students’ questions compared with human professors.

(00:15:18) Surprising Results

Why AI answers were often preferred 

(00:16:16) What the Study Shows

The findings support AI tutoring, but don’t prove AI improves learning.

(00:18:48) Limits of One-Shot Answers

Why real teaching often depends on dialogue, clarification, and productive struggle.

(00:20:59) AI for Social Science

How AI can become both an object of study and a tool.

(00:22:43) Research Agents

Using AI to test