All rise for JudgeGPT

"In her current job, McCormack is working on a new kind of legal decision-maker. Like a judge, it would make mistakes. But unlike many judges, it wouldn't be burdened by more casework than it had hours in the day. It could make sure to always show its work, check that each side agreed it understood all the facts, and ensure it ruled on each issue at play. And it wouldn't be human - it's made of neural networks."

"McCormack leads the American Arbitration Association, which has developed an AI Arbitrator to help parties settle document-based disputes in a low-cost way. The system is built on OpenAI's models to walk parties in arbitration through their dispute and draft a decision on who should win the case and why. The system deals only with cases that rely solely on documents, and there's a human in the loop at every stage, including in the final step of issuing an award."

"Last year, at least two federal judges had to issue mea culpas and come up with new policies after issuing court orders with made-up facts, thanks to the use of generative AI. Academics warn that AI's legal interpretations are not as straightforward as they can seem, and can either introduce false information or rely on sources that would never be legally admissible otherwise."

Bridget McCormack previously reviewed lower-court judicial complaints and now leads the American Arbitration Association's development of an AI Arbitrator. The system, based on OpenAI models, guides parties through document-only arbitrations, drafts decisions explaining who should prevail and why, and keeps a human involved at every stage including the award. The design aims to show work, confirm factual understanding between parties, and rule on each issue to increase speed, lower costs, and improve access to dispute resolution. Generative AI has produced courtroom errors, introduced false or inadmissible sources, and can amplify human biases, raising concerns about accuracy and public trust.

Read at The Verge