On Friday, December 6, 2024, the Learning Informatics Lab hosted Dr. Harmanpreet Kaur from the University of Minnesota. In this talk, Dr. Kaur discussed her research on explainable AI and why it does not work in practice. She also shared design ideas—both completed and current work—to help people with varying expertise understand AI outputs.
Author: LI Lab
Fall ’24 Colloquium: Leveraging Social Theories to Enhance Human-AI Interaction
Date: Friday, December 6
Time: 4:00 – 5:00 PM (Central Time)
Location: Education Sciences Building, Room 325
Featured Speaker: Dr. Harmanpreet Kaur (She/Her)
Assistant Professor, Department of Computer Science & Engineering
Dr. Harmanpreet Kaur is a leading researcher in human-centered artificial intelligence (AI), focusing on explainability, interpretability, and hybrid intelligence systems.
Talk OVERVIEW
As human-AI partnerships become more prevalent, their effectiveness hinges on addressing critical challenges like dynamic human needs and AI’s opaque reasoning. Many current systems fail to explain AI decision-making clearly, often perpetuating biases and overlooking nuanced edge cases.
Dr. Kaur will explore why explainable AI often falls short in practical applications and discuss innovative designs—both completed and ongoing—that aim to empower users with varying levels of expertise to better understand and interact with AI outputs.