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Principles of Explanation in Human-AI Systems
XAI systems are frequently algorithm-focused; starting and ending with an algorithm that implements a basic untested idea about explainability.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
Explaining AI as an Exploratory Process: The Peircean Abduction Model
It might be worthwhile to pursue this, to develop intelligent systems that allow for the observation and analysis of abductive reasoning and the assessment of abductive reasoning as a learnable skill.
Cognitive Anthropomorphism of AI: How Humans and Computers Classify Images
Modern AI image classifiers have made impressive advances in recent years, but their performance often appears strange or violates expectations of users.
Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI
That said, most of the key concepts and issues are expressed in this Report.
Metrics for Explainable AI: Challenges and Prospects
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 pragmatic understanding of the AI?
