Event Details

Speaker: John Licato, University of South Florida

Location: Virtual Only via Zoom

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Meeting ID: 960 7692 7864

Passcode: 810249

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Although it is now incredibly easy to create and deploy a chatbot for almost any application, powered by highly capable LLMs, even the best systems still tend to perform poorly when they need to interpret and reason about rules—specifically, rules expressed in the kind of language found in laws, contracts, regulations, and the like. Why does this problem still exist, and how can it be overcome? Dr. Licato argues that the problem is rooted in a feature (not a bug) of human languages called open-texturedness. And this open-texturedness, because it is an inevitable feature of normative rule systems, must be addressed by any agent-level AI system, especially if we want it to be able to follow our laws.

Speaker Bio

John Licato, PhD is an Associate Professor of Computer Science and Engineering at USF, Director of the USF Advancing Machine and Human Reasoning (AMHR) Lab, and founder of AI startup Actualization AI, LLC. He designed and teaches the natural language processing course (the field that created ChatGPT) at USF, and his lab's mission is to not only make AI smarter, but to use those advances to make people reason better as well. His research expertise lies in AI, NLP, human reasoning, cognitive modeling, and legal / regulatory reasoning, with over 100 peer-reviewed publications. He has been featured in outlets such as NPR's Marketplace Tech, ABC Action News, and the Tampa Bay Business Journal.

Host: Abel Salinas, POC: Pete Zamar

If speaker approves to be recorded for this AI Seminar talk, it will be posted on our USC/ISI YouTube page within 1-2 business days: https://www.youtube.com/user/USCISI.