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To act safely and ethically in the real world, agents must be able to reason about harm and avoid harmful actions.
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Tom Everitt, Ramana Kumar, Victoria Krakovna, and Shane Legg · 2019
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Silvia Chiappa · 2019
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Judea Pearl · 2019
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Max Kleiman-Weiner, Tobias Gerstenberg, Sydney Levine, and Joshua B Tenenbaum · 2015
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Causal inference in statistics, social, and biomedical sciences
Guido W Imbens and Donald B Rubin · 2015
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A modification of the halpern-pearl definition of causality
Joseph Halpern · 2015
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Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner · 2016
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Joseph Y Halpern · 2016
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Causal inference for recommendation
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Prediction of disease progression in multiple sclerosis patients using deep learning analysis of mri data
Adrian Tousignant, Paul Lemaître, Doina Precup, Douglas L Arnold, and Tal Arbel · 2019
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Artificial intelligence, bias and clinical safety
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On pearl’s hierarchy and the foundations of causal inference
Elias Bareinboim, Juan D Correa, Duligur Ibeling, and Thomas Icard · 2020
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Explainable reinforcement learning through a causal lens
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Jonathan G Richens, Ciarán M Lee, and Saurabh Johri · 2020
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Counterfactual vision-and-language navigation: Unravelling the unseen
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Causal inference and counterfactual prediction in machine learning for actionable healthcare
Mattia Prosperi, Yi Guo, Matt Sperrin, James S Koopman, Jae S Min, Xing He, Shannan Rich, Mo Wang, Iain E Buchan, and Jiang Bian · 2020
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Niki Kilbertus, Philip J Ball, Matt J Kusner, Adrian Weller, and Ricardo Silva · 2020
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Reinforcement learning for clinical decision support in critical care: comprehensive review
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Algorithmic justice: Algorithms and big data in criminal justice settings
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Reward tampering problems and solutions in reinforcement learning: A causal influence diagram perspective
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Counterfactual vqa: A cause-effect look at language bias
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Generate your counterfactuals: Towards controlled counterfactual generation for text
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From real-world patient data to individualized treatment effects using machine learning: Current and future methods to address underlying challenges
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Toward causal representation learning
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A counterfactual simulation model of causal judgments for physical events
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A structural causal model for mr images of multiple sclerosis
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Counterfactual explanations in sequential decision making under uncertainty
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Reinforcement learning in healthcare: A survey
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Ethical and social risks of harm from language models
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A survey on bias and fairness in machine learning
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Path-specific objectives for safer agent incentives
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