M.C. Schraefel, Josh Andrés, et al.
CHI EA 2021
As Artificial Intelligence technologies are increasingly used to make important decisions and perform autonomous tasks, providing explanations to allow users and stakeholders to understand the AI has become a ubiquitous concern. Recently, a number of open-source toolkits are making the growing collection of Explainable AI (XAI) techniques accessible for researchers and practitioners to incorporate explanation features in AI systems. This course is open to anyone interested in implementing, designing and researching on the topic, aiming to provide an overview on the technical and design methods for XAI, as well as hands-on experience with an XAI toolkit.
M.C. Schraefel, Josh Andrés, et al.
CHI EA 2021
Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, et al.
NeurIPS 2023
Gaetano Rossiello, Nhan Pham, et al.
ICLR 2025
Balaji Ganesan, Hima Patel, et al.
NeurIPS 2020