Artificial intelligence has permeated most aspects of society, and the legal system is no exception. Today, every step of criminal justice, from the police investigation to the trial, can — and often does — involve AI. That change comes with many implications, some of them desirable and some less so. Last month, three SFI Faculty — Resident Professors Cristopher Moore and Melanie Mitchell, and External Professor Melanie Moses, a distinguished professor of computer science from the University of New Mexico — addressed these implications during panel discussions at the National Judicial Summit on the Foundation and Future of the Judiciary, held in Santa Fe. Around 300 judges attended the summit, with two-thirds of the participants coming from New Mexico. The additional hundred judges represented 22 different states and eight tribal nations. Two guests of SFI also participated in the panel discussions: Berkeley law professor Andrea Roth and Maryland public defender Marc Canellas. Both are experts on AI-generated evidence who also attended a 2025 SFI working group on AI and Justice supported by the Robert Wood Johnson Foundation through SFI’s Emergent Engineering project. The professors’ goal was to give judges a realistic view of how AI can expedite their work while also warning them of pitfalls they might encounter. “If judges and juries are dazzled by the technology, it’s going to be hard for them to think critically about the evidence,” says Moore. “I want people to understand that AI has strengths, and it has weaknesses.” For example, AI has made facial-recognition technology much more effective. But when using this technology, police need to balance the need to catch criminals with the expectation of privacy. “Do we want cameras on every street corner that are constantly watching us?” Moore asks. “That’s a policy question, and I think a very important one.”