All day
AI is impacting high-stakes decisions across society, in domains like health, housing, and hiring. But the justice system, perhaps more than any other domain, demands things like procedural fairness, individualized justice, transparency, and contestability—values that can’t be captured by statistical notions of accuracy or fairness. This workshop will examine the uses and misuses of AI in criminal justice, ranging from risk assessment and forensic evidence to uses of general purpose AI for open-ended tasks such as examining police reports and court transcripts. Where is the frontier in this field? What kind of transparency do AI tools need to have to be used in the justice system? Can we convince judges or legislatures to demand independent testing of software? In the absence of Federal legislation, what kinds of laws are state legislatures considering? What role can “soft law” and professional organizations play? And what would it mean to do AI “right” in this area?
Organizers
Cristopher Moore
Melanie MosesProfessor of Computer Science, University of New Mexico; External Professor at SFI
Kristian LumResearch Scientist at Google DeepMind
Andrea RothProfessor of Law and Barry Tarlow Chancellor's Chair in Criminal Justice
David BallProfessor, Santa Clara School of Law
Marc CanellasPublic Defender in the Forensics Division of the Maryland Office of the Public Defender
Sam ZhangAssistant Professor of Statistics at the Complex Systems Center at the University of Vermont