David Jensen, UMass Amherst
Thursday, November 09
Public Talk @ 7:30pm
Bronfman Auditorium (Wachenheim B11)
***CS Colloquium credit for attendance. Reception to follow***
What’s So Important About Explanation? Science, Machine Learning, and Large Language Models
Large language models (LLMs), and systems derived from these models such as ChatGPT and Bard, are widely perceived as an unexpected and transformative leap forward in artificial intelligence (AI). This has elevated concerns about the potential near-term impacts of AI, and it has produced calls for immediate regulation of these technologies. However, our ability to forecast social impacts and craft appropriate public policies depends critically on the underlying science — what is known about how these technologies work and what they can actually do. In this talk, I will explore some of what is known about LLMs and how we know it. I will describe some of the scientific, institutional, and economic barriers to effective research on LLMs, and how this affects our ability to effectively manage and regulate this crucial class of technologies.
David Jensen is Professor of Computer Science in the College of Information and Computer Sciences at the University of Massachusetts Amherst. His research focuses on machine learning, causal modeling, and research methods in computer science. His work aims to improve the analysis of large social, technological, and computational systems, with the goals of furthering prediction, explanation, security, and policy decisions. From 2018 to 2022, he served as Director of the Computational Social Science Institute, an interdisciplinary effort at UMass to study social phenomena using computational tools and concepts. From 1991 to 1995, he served as an analyst with the Office of Technology Assessment, an agency of the United States Congress. He regularly serves on program committees the Conference on Neural Information Processing Systems, the International Conference on Machine Learning, and the AAAI Conference on Artificial Intelligence. He has served on the Defense Science Study Group (2006-2007) and DARPA’s Information Science and Technology Group (2007-2012). He currently serve on the Computing Community Consortium (CCC) Council, the research visioning arm of the Computing Research Association. He received outstanding teaching awards from the UMass College of Natural Sciences in 2011 and from the College of Information and Computer Sciences in 2022. In 2017, one of his papers received the IEEE INFOCOM Test of Time Paper Award.