Measures for explainable AI: Explanation goodness, user satisfaction, mental models, curiosity, trust, and human-AI performance

If a user is presented an AI system that portends to explain how it works, how do we know whether the explanation works and the user has achieved a pragmatic understanding of the AI? This question entails some key concepts of measurement such as explanation goodness and trust. We present methods for...

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Veröffentlicht in:	Frontiers in computer science (Lausanne) Jg. 5
Hauptverfasser:	Hoffman, Robert R., Mueller, Shane T., Klein, Gary, Litman, Jordan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Frontiers Media S.A 06.02.2023
Schlagworte:	explanation goodness explanatory reasoning machine-generated explanations measurement mental models trust
ISSN:	2624-9898, 2624-9898
Online-Zugang:	Volltext
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