Research
Empirical and applied research on how AI affects legal education and practice.
The Lab’s research pillar studies what AI can and cannot do in law school, in practice, and on the bench. We run controlled experiments, analyze data from real teaching environments, and produce empirical findings that inform what gets built next.
The research feeds the rest of the Lab: findings shape what the Build pillar makes, and what the Teach pillar takes out into the field. The loop closes when teaching and tool use surface the next questions worth studying.
Projects in Research
Workstreams the Lab is running under the research pillar — including projects that span multiple pillars.
Exam Grader
Calibration-based AI grading for law-school essay exams — deployed against Polk's Spring 2026 IP class.
Exam Taker
Wave 2 of the AI Final Exam Project — putting current models against real Penn Carey Law finals and reporting what they can and can't do.
Class Simulations
AI-driven simulations built around the actual class problems law students work through each week — starting with patent law.