Melanie MITCHELL – 19 octobre 2023
Titre : The Debate Over “Understanding” in AI’s Large Language Models
I will survey a current, heated debate in the AI research community on whether large pre-trained language models can be said -- in any important sense -- to "understand" language and the physical and social situations language encodes. I will describe arguments that have been made for and against such understanding, and, more generally, will discuss what methods can be used to fairly evaluate understanding and intelligence in AI systems. I will conclude with key questions for the broader sciences of intelligence that have arisen in light of these discussions.
Melanie Mitchell is Professor at the Santa Fe Institute. Her current research focuses on conceptual abstraction and analogy-making in artificial intelligence systems. Melanie 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) is a finalist for the 2023 Cosmos Prize for Scientific Writing.
Mitchell, M. (2023). How do we know how smart AI systems are? Science, 381(6654), adj5957.
Mitchell, M., & Krakauer, D. C. (2023). The debate over understanding in AI’s large language models. Proceedings of the National Academy of Sciences, 120(13), e2215907120.
Millhouse, T., Moses, M., & Mitchell, M. (2022). Embodied, Situated, and Grounded Intelligence: Implications for AI. arXiv preprint arXiv:2210.13589.