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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

Showing 376400 of 971 papers

TitleStatusHype
Analysis and Evaluation of Explainable Artificial Intelligence on Suicide Risk Assessment0
A Complete Characterisation of ReLU-Invariant Distributions0
Counterfactual and Semifactual Explanations in Abstract Argumentation: Formal Foundations, Complexity and Computation0
Correlation between morphological evolution of splashing drop and exerted impact force revealed by interpretation of explainable artificial intelligence0
A Survey of Explainable Knowledge Tracing0
Regularizing Explanations in Bayesian Convolutional Neural Networks0
Convolutional Neural Network Interpretability with General Pattern Theory0
A Survey of Explainable Artificial Intelligence (XAI) in Financial Time Series Forecasting0
Contextual Trust0
A Survey of Explainable AI and Proposal for a Discipline of Explanation Engineering0
Explainable Artificial Intelligence Model for Evaluating Shear Strength Parameters of Municipal Solid Waste Across Diverse Compositional Profiles0
A Survey of Accessible Explainable Artificial Intelligence Research0
A Multi-Modal Explainability Approach for Human-Aware Robots in Multi-Party Conversation0
Explainable artificial intelligence in breast cancer detection and risk prediction: A systematic scoping review0
Explainable Artificial Intelligence in Biomedical Image Analysis: A Comprehensive Survey0
Explainable Artificial Intelligence in Retinal Imaging for the detection of Systemic Diseases0
Concept Induction using LLMs: a user experiment for assessment0
Asset Pricing and Deep Learning0
Explainable Artificial Intelligence in Construction: The Content, Context, Process, Outcome Evaluation Framework0
Enabling Verification of Deep Neural Networks in Perception Tasks Using Fuzzy Logic and Concept Embeddings0
Shapley values for cluster importance: How clusters of the training data affect a prediction0
Explainable Artificial Intelligence for Smart City Application: A Secure and Trusted Platform0
Explainable Artificial Intelligence Methods in Combating Pandemics: A Systematic Review0
Concept Embedding Analysis: A Review0
Assessing high-order effects in feature importance via predictability decomposition0
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