Promises and Pitfalls of Artificial Intelligence for Legal Applications

Date: October 18, 2024 (Friday)
Time: 7pm to 8:30pm
Venue: Room 824, 8/F Cheng Yu Tung Tower, The University of Hong Kong
Speaker: Sayash Kapoor (Ph.D. Candidate, Center for Information Technology Policy, Princeton University)
Moderator: Benjamin Chen (Director of Law and Technology Centre & Associate Professor, The University of Hong Kong Faculty of Law)
Abstract:
Is AI set to redefine the legal profession? In this talk, we will see why claim is not supported by the current evidence. We will dive into AI’s increasingly prevalent roles in three types of legal tasks: information processing; tasks involving creativity, reasoning, or judgment; and predictions about the future. The ease of evaluating legal applications varies greatly across legal tasks, based on the ease of identifying correct answers and the observability of information relevant to the task at hand. Tasks that would lead to the most significant changes to the legal profession are also the ones most prone to overoptimism about AI capabilities, as they are harder to evaluate. We will conclude with recommendations for better evaluation and deployment of AI in legal contexts.
About the speaker:
Sayash Kapoor is a Laurance S. Rockefeller Graduate Prize Fellow in the University Center for Human Values and a computer science Ph.D. candidate at Princeton University’s Center for Information Technology Policy. He is a coauthor of AI Snake Oil, a book that provides a critical analysis of artificial intelligence, separating the hype from the true advances. His research examines the societal impacts of AI, with a focus on reproducibility, transparency, and accountability in AI systems. He is especially interested in the interaction between AI and policy. He has previously worked on AI in various institutions in academia and the industry, including at Facebook, Columbia University, and EPFL Switzerland. Kapoor has been recognized with various awards, including a best paper award at ACM FAccT, an impact recognition award at ACM CSCW, and inclusion in TIME’s inaugural list of the 100 most influential people in AI.