TREX 2021:
Workshop on TRust and EXpertise
in Visual Analytics

Human-Centered Explainable AI (HCXAI): From Algorithms to User Experiences

Dr. Q. Vera Liao - Microsoft Research

Abstract: As a technical sub-field of artificial intelligence (AI), explainable AI (XAI) has produced a vast collection of algorithms in recent years. However, explainability is an inherently human-centric property and the field is starting to embrace human-centered approaches. HCI research and UX design in this area are increasingly important especially as practitioners begin to leverage XAI algorithms to build XAI applications. In this talk, I will draw on our own research and broad HCI work to highlight the central role that human-centered approaches should play in shaping XAI technologies, including to drive technical choices by understanding user needs, to uncover pitfalls of existing XAI methods, and to provide conceptual frameworks for human-compatible XAI.

Bio: Q. Vera Liao is a Principal Researcher at Microsoft Research Montreal. Her current interest is in human-AI interaction and explainable AI, with a focus on bridging state-of-the-art AI technologies and user-centered design practices. She serves as the Co-Editor-in-Chief for Springer HCI Series, and on the Editorial Board of IJHCS and ACM TiiS. Before joining MSR, she worked at IBM T.J. Watson Research Center.