Stanford Law School will host a cross-disciplinary dinner on May 26, 2026, bringing computer science and law students together to examine how AI intersects with legal practice. The event runs from 5:45 PM to 8:00 PM in Room 270 at Stanford Law School, with dinner served at 5:45 PM and programming from 6:15 PM onward.
The evening is co-hosted by CodeX and the Stanford AI Initiative. It is open to both CS and law students, with no prior expertise required on either side.
Two fields, one conversation
The event is structured around a simple exchange. CS students explain how large language models actually work and where they fail. Law students explain the values and realities of legal practice. Then the two groups sit down together at roundtables split half CS and half law, guided by discussion cards covering questions like who is liable when AI causes harm, and what the biggest problems in generative AI are today.
The stated goal is to spark the conversations that don't usually happen between these two groups. For CS students, the hook is that law represents one of the most demanding and consequential use cases for AI: high-stakes reasoning, adversarial contexts, and zero tolerance for hallucination. For law students, the pitch is direct: the people building AI tools are one room away, and the evening offers a chance to see what LLMs can and can't do up close.
Structure of the evening
The program opens with two short presentations, one from each side. After the roundtable discussions, the event closes with open networking and a chance for students to ask each other anything. For CS and law students alike, the event offers a practical way to build connections early - including familiarity with how AI for legal work is actually being discussed and built.
Students on the law side might want to walk in with a clear question: what the field's adoption of Generative AI and LLM tools means for their practice. Students on the CS side may want to ask what constraints legal practice actually places on model deployment, and where reliability matters most.
Why this matters for legal practitioners
Law students and early-career lawyers will be working alongside AI systems in nearly every setting, from document review to research. Having a working sense of how these models are built - and where they trust - will separate lawyers who can evaluate AI output from those who just accept it. An evening like this is a direct shortcut: it compresses the time it normally takes to learn the other side's priorities, and makes the tradeoffs of deploying AI in legal work visible to both groups.
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