|Talks|

Why is it so Hard to Understand AI?

Visiting speaker
Hybrid
Past Talk
David Jensen
Professor Manning College of Information & Computer Sciences University of Massachusetts Amherst
Wed
,
Nov 4, 2026
1:00 pm
EST
Nov 4, 2026
1:00 pm
In-person
Portsoken Street
London, E1 8PH, UK
The Roux Institute
Room
100 Fore Street
Portland, ME 04101
Network Science Institute
2nd floor
Network Science Institute
11th floor
177 Huntington Ave
Boston, MA 02115
Network Science Institute
2nd floor
Rm 140 Open Space, 4th Floor, 101 BV
Room
58 St Katharine's Way
London E1W 1LP, UK
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Talk recording

Large language models (LLMs) and other foundation models have enabled a set of unexpected and socially transformative AI technologies. This has elevated concerns about the potential near-term impacts of AI and produced calls for immediate regulation of these technologies. However, our ability to forecast the impacts of AI and craft appropriate responses depends critically on the underlying science — what is known about fundamental computational mechanisms that enable model capabilities, how AI systems will respond to varying inputs and contexts, and how these systems can be guided and controlled. Unfortunately, scientific research in modern AI is hindered by a set of scientific, institutional, and economic challenges. Taken together, these challenges present barriers to understanding that are unprecedented in the history of modern science.

About the speaker
David Jensen is Professor of Computer Science in the Manning 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. From 2018 to 2022, he served as Director of the UMass Computational Social Science Institute, an interdisciplinary effort 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 currently serves as the vice-chair of the Computing Community Consortium (CCC) Council, the research visioning arm of the Computing Research Association. He has received two college-wide outstanding teaching awards at UMass, and he has published over 100 peer-reviewed papers in machine learning and AI.
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Nov 04, 2026