Visualization by Olivia Seow
Abstract
A primary barrier to using artificial intelligence is a proper understanding of how the system works, which enables trusts. To confront this, explainable visualizations provide a scaffolding for providing transparency to users. In order to provide this equitably, explainable visualizations should balance completeness and interpretability.
Paper by Olivia Seow, Dave Ludgin, and John Liu
Video
NV Labs, Rich Harris, Sam Learner, and Derrick Schultz for the data and code references