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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 326–350 of 971 papers

TitleStatusHype
Automated detection of motion artifacts in brain MR images using deep learning and explainable artificial intelligence—0
Détection d'objets célestes dans des images astronomiques par IA explicable—0
AUTOLYCUS: Exploiting Explainable AI (XAI) for Model Extraction Attacks against Interpretable Models—0
A New Perspective on Evaluation Methods for Explainable Artificial Intelligence (XAI)—0
Adversarial Attack for Explanation Robustness of Rationalization Models—0
Detecting Anomalies in Blockchain Transactions using Machine Learning Classifiers and Explainability Analysis—0
Detecting AI-Generated Text in Educational Content: Leveraging Machine Learning and Explainable AI for Academic Integrity—0
A User-Centred Framework for Explainable Artificial Intelligence in Human-Robot Interaction—0
Designing Explainable Predictive Machine Learning Artifacts: Methodology and Practical Demonstration—0
Designing explainable artificial intelligence with active inference: A framework for transparent introspection and decision-making—0
A Unified Framework for Evaluating the Effectiveness and Enhancing the Transparency of Explainable AI Methods in Real-World Applications—0
A New Deep Learning and XAI-Based Algorithm for Features Selection in Genomics—0
Designing ECG Monitoring Healthcare System with Federated Transfer Learning and Explainable AI—0
Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma—0
Augmented cross-selling through explainable AI -- a case from energy retailing—0
Advancing Nearest Neighbor Explanation-by-Example with Critical Classification Regions—0
Deep Unsupervised Identification of Selected SNPs between Adapted Populations on Pool-seq Data—0
Deep Learning Reproducibility and Explainable AI (XAI)—0
Audio-visual cross-modality knowledge transfer for machine learning-based in-situ monitoring in laser additive manufacturing—0
Deep Learning, Natural Language Processing, and Explainable Artificial Intelligence in the Biomedical Domain—0
Deep Learning for predicting rate-induced tipping—0
A Turing Test for Transparency—0
Attributions Beyond Neural Networks: The Linear Program Case—0
Deciphering knee osteoarthritis diagnostic features with explainable artificial intelligence: A systematic review—0
A Transformer variant for multi-step forecasting of water level and hydrometeorological sensitivity analysis based on explainable artificial intelligence technology—0
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