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Explainable artificial intelligence

XAI refers to methods and techniques in the application of artificial intelligence (AI) such that the results of the solution can be understood by humans. It contrasts with the concept of the "black box" in machine learning where even its designers cannot explain why an AI arrived at a specific decision. XAI may be an implementation of the social right to explanation. XAI is relevant even if there is no legal right or regulatory requirement—for example, XAI can improve the user experience of a product or service by helping end users trust that the AI is making good decisions. This way the aim of XAI is to explain what has been done, what is done right now, what will be done next and unveil the information the actions are based on. These characteristics make it possible (i) to confirm existing knowledge (ii) to challenge existing knowledge and (iii) to generate new assumptions.

Papers

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Showing 426–450 of 971 papers

TitleStatusHype
Achieving Diversity in Counterfactual Explanations: a Review and Discussion—0
A Survey on Understanding, Visualizations, and Explanation of Deep Neural Networks—0
Analysis of Explainable Artificial Intelligence Methods on Medical Image Classification—0
Explainable Goal-Driven Agents and Robots -- A Comprehensive Review—0
Explainable Image Recognition via Enhanced Slot-attention Based Classifier—0
Explainable Incipient Fault Detection Systems for Photovoltaic Panels—0
Explainable Interface for Human-Autonomy Teaming: A Survey—0
Explainable Knowledge Distillation for On-device Chest X-Ray Classification—0
Explainable Label-flipping Attacks on Human Emotion Assessment System—0
A Systematic Review of User-Centred Evaluation of Explainable AI in Healthcare—0
Explainable Lung Disease Classification from Chest X-Ray Images Utilizing Deep Learning and XAI—0
Explainable Machine Learning-Based Security and Privacy Protection Framework for Internet of Medical Things Systems—0
Data integration in systems genetics and aging research—0
Explainable Machine Learning for Predicting Homicide Clearance in the United States—0
Explainable Artificial Intelligence (XAI) for Malware Analysis: A Survey of Techniques, Applications, and Open Challenges—0
Explainable Multi-Label Classification of MBTI Types—0
Explainable Multimodal Sentiment Analysis on Bengali Memes—0
Explainable Predictive Maintenance—0
Explainable Reinforcement Learning: A Survey—0
Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey—0
Explainable Reinforcement Learning on Financial Stock Trading using SHAP—0
Explaining machine learning models for age classification in human gait analysis—0
A general approach to compute the relevance of middle-level input features—0
Explaining AI Decisions: Towards Achieving Human-Centered Explainability in Smart Home Environments—0
Explaining the Deep Natural Language Processing by Mining Textual Interpretable Features—0
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