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Causality and eXplainable Artificial Intelligence (XAI) have developed as separate fields in computer science, even though the underlying concepts of causation and explanation share common ancient roots.
Studies in the logic of explanation
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Explanatory scope informs causal strength inferences, in: Proceedings of the Annual Meeting of the Cognitive Science Society
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A survey of methods for explaining black box models
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Causal structure learning
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Tetrad—a toolbox for causal discovery, in: 8th International Workshop on Climate Informatics
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Explainable artificial intelligence for human-centric data analysis in virtual learning environments, in: Higher Education Learning Methodologies and Technologies Online: First International Workshop, HELMeTO 2019, Novedrate, CO, Italy, June 6-7, 2019, Revised Selected Papers 1, Springer. pp. 125–138
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Explainable artificial intelligence for safe intraoperative decision support
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An engineer’s guide to explainable artificial intelligence and interpretable machine learning: Navigating causality, forced goodness, and the false perception of inference
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The seven tools of causal inference, with reflections on machine learning
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Natural language generation challenges for explainable ai, in: 1st Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence
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Arrieta, A.B., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., García, S., Gil-López, S., Molina, D., Benjamins, R., et al., 2020 · 2020
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Temporal causal inference in wind turbine scada data using deep learning for explainable ai, in: Journal of Physics: Conference Series, IOP Publishing. p. 022022
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Beyond deep event prediction: Deep event understanding based on explainable artificial intelligence
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Toward causal representation learning
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Demonstration of generating explanations for black-box algorithms using lewis
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Can robots do epidemiology? machine learning, causal inference, and predicting the outcomes of public health interventions
Broadbent, A., Grote, T., 2022 · 2022
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Counterfactuals and causability in explainable artificial intelligence: Theory, algorithms, and applications
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Crupi, R., González, B.S.M., Castelnovo, A., Regoli, D., 2022 · 2022
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