Results 11 to 20 of about 27,667 (170)
To explain or not to explain?—Artificial intelligence explainability in clinical decision support systems [PDF]
PLOS Digital Health, 2022 Explainability for artificial intelligence (AI) in medicine is a hotly debated topic. Our paper presents a review of the key arguments in favor and against explainability for AI-powered Clinical Decision Support System (CDSS) applied to a concrete use case, namely an AI-powered CDSS currently used in the emergency call setting to identify patients with
Julia Amann +14 more
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Explaining norms and norms explained [PDF]
Behavioral and Brain Sciences, 2009 AbstractOaksford & Chater (O&C) aim to provide teleological explanations of behavior by giving an appropriate normative standard: Bayesian inference. We argue that there is no uncontroversial independent justification for the normativity of Bayesian inference, and that O&C fail to satisfy a necessary condition for teleological explanations:
Danks, David, Eberhardt, Frederick
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To explain or not to explain [PDF]
Proceedings of the 24th International Conference on Intelligent User Interfaces, 2019 Recommender systems have been increasingly used in online services that we consume daily, such as Facebook, Netflix, YouTube, and Spotify. However, these systems are often presented to users as a "black box", i.e. the rationale for providing individual recommendations remains unexplained to users.
Millecamp, Martijn +3 more
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Can Explainable AI Explain Unfairness? A Framework for Evaluating Explainable AI
CoRR, 2021 Many ML models are opaque to humans, producing decisions too complex for humans to easily understand. In response, explainable artificial intelligence (XAI) tools that analyze the inner workings of a model have been created. Despite these tools' strength in translating model behavior, critiques have raised concerns about the impact of XAI tools as a ...
Kiana Alikhademi +3 more
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Journal of Perinatal Education, 2005 Childbirth educator humorously discusses props used as tools for teaching and teasing.
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Explaining Simulations Through Self Explaining Agents [PDF]
Journal of Artificial Societies and Social Simulation, 2010 Several strategies are used to explain emergent interaction patterns in agent-based simulations. A distinction can be made between simulations in which the agents just behave in a reactive way, and simulations involving agents with also pro-active (goal-directed) behavior.
Maaike Harbers +2 more
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Explaining visual counterfactual explainers
Trans. Mach. Learn. Res., 2023 Altres ajuts: this work was supported by the Generalitat de Catalunya under the Industrial Doctorate Program (grant number 2020DI62).
Velazquez Dorta, Diego Alejandro +5 more
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Cognitive Science, 1994 Emotions and cognition are inextricably intertwined. Feelings influence thoughts and actions, which in turn can give rise to new emotional reactions. We claim that people infer emotional states in others using commonsense psychological theories of the interactions among emotions, cognition, and action.
Paul O'Rorke, Andrew Ortony
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Proceedings of the 1st International Conference on Explainable AI for Neural and Symbolic MethodsExplanation is key to people having confidence in high-stakes AI systems. However, machine-learning-based systems -- which account for almost all current AI -- can't explain because they are usually black boxes. The explainable AI (XAI) movement hedges this problem by redefining "explanation".
Sergei Nirenburg +3 more
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What Is the Role of Explainability in Medical Artificial Intelligence? A Case-Based Approach
BioengineeringThis article reflects on explainability in the context of medical artificial intelligence (AI) applications, focusing on AI-based clinical decision support systems (CDSS).
Elisabeth Hildt
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