222 citations · 449 across the 3 of their papers we have counts for
3 papers
Principles of Explanation in Human-AI Systems
Shane T. Mueller, Elizabeth S. Veinott, Robert R. Hoffman +4
Explainable Artificial Intelligence (XAI) has re-emerged in response to the development of modern AI and ML systems. These systems are complex and sometimes biased, but they nevert…
Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI
Shane T. Mueller, Robert R. Hoffman, William Clancey +2
This is an integrative review that address the question, "What makes for a good explanation?" with reference to AI systems. Pertinent literatures are vast. Thus, this review is nec…
Metrics for Explainable AI: Challenges and Prospects
Robert R. Hoffman, Shane T. Mueller, Gary Klein +1
The question addressed in this paper is: If we present to a user an AI system that explains how it works, how do we know whether the explanation works and the user has achieved a p…