Melanie Mitchell: AI's Challenge to Understanding the World

PLENARY SESSION 6 | Thursday, August 22, 17:30-18:45 | Auditorium 1 (1441-011)


Melanie Mitchell is Professor at the Santa Fe Institute, USA. Her current research focuses on conceptual abstraction and analogy-making in artificial intelligence systems.  Prof. Mitchell is the author or editor of six books and numerous scholarly papers in the fields of artificial intelligence, cognitive science, and complex systems. Her 2009 book Complexity: A Guided Tour (Oxford University Press) won the 2010 Phi Beta Kappa Science Book Award, and her 2019 book Artificial Intelligence: A Guide for Thinking Humans (Farrar, Straus, and Giroux) was shortlisted for the 2023 Cosmos Prize for Scientific Writing. She is the recipient of the Senior Scientific Award from the Complex Systems Society, the Distinguished Cognitive Scientist Award from UC Merced, and the Herbert A. Simon Award of the International Conference on Complex Systems. Prof.Mitchell originated the Santa Fe Institute's Complexity Explorer platform, which offers online courses and other educational resources related to the field of complex systems. Her online course Introduction to Complexity was named one of Class Central’s "Best Free Online Courses of All Time."

Abstract of lecture

I will survey a debate in the artificial intelligence (AI) research community on the extent to which current AI systems can be said to “understand” language and the physical and social situations language encodes. I will describe arguments that have been made for and against such understanding, hypothesize about what humanlike understanding entails, and discuss what methods can be used to fairly evaluate understanding and intelligence in AI systems. 

Plenary dialogue

Professor Mitchell will deliver her lecture remotely and then engage in a live dialogue with two interlocutors before addressing questions from the audience. Moderator: TBA.

Interlocutor 1: Selmer Bringsjord, Rensselaer Polytechnic Institute, USA

Selmer Bringsjord specializes in the logico-mathematical and philosophical foundations of artificial intelligence (AI) and cognitive science (CogSci), in collaboratively building AI systems/cognitive robots on the basis (primarily) of computational logic, and in the logic-based and theorem-guided modeling and simulation of rational, human-level-and-above cognition. 

Interlocutor 2: Robin Zebrowski, Beloit College in Wisconsin, USA

Robin L. Zebrowski is Professor and Chair of Cognitive Science at Beloit College in Wisconsin, USA. She holds a joint appointment in Philosophy, Psychology, and Computer Science. Her work focuses on 4E cognition in relation to artificial intelligence and cyborg technologies, with an increasing focus on social cognition. Her most recent work involves reconciling the problems of anthropomorphism in humanoid robotics with enactive and embodied theories of mind, as well as understanding the role and possibility of technology-mediated interactions within enactive social cognition.