Automated Explanation Selection for Scientific Discovery
Automated reasoning is a key technology in the young but rapidly growing field of Explainable Artificial Intelligence (XAI). Explanability helps build trust in artificial intelligence systems beyond their mere predictive accuracy and robustness. In this paper, we propose a cycle of scientific discovery that combines machine learning with automated reasoning for the generation and the selection of explanations. We present a taxonomy of explanation selection problems that draws on insights from sociology and cognitive science. These selection criteria subsume existing notions and extend them with new properties.
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Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)scientific discoverySociologySimilar Papers 제목 키워드 기반
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