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Human performance consequences of normative and contrastive explanations: An experiment in machine learning for reliability maintenance
Artificial Intelligence 321 (C):103945 (2023)
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References found in this work
Explanation in artificial intelligence: Insights from the social sciences.Tim Miller - 2019 - Artificial Intelligence 267 (C):1-38.
What do we want from Explainable Artificial Intelligence (XAI)? – A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research.Markus Langer, Daniel Oster, Timo Speith, Lena Kästner, Kevin Baum, Holger Hermanns, Eva Schmidt & Andreas Sesing - 2021 - Artificial Intelligence 296 (C):103473.
Evaluating XAI: A comparison of rule-based and example-based explanations.Jasper van der Waa, Elisabeth Nieuwburg, Anita Cremers & Mark Neerincx - 2021 - Artificial Intelligence 291 (C):103404.
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