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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 7180 of 971 papers

TitleStatusHype
PixleepFlow: A Pixel-Based Lifelog Framework for Predicting Sleep Quality and Stress LevelCode0
This looks like what? Challenges and Future Research Directions for Part-Prototype ModelsCode0
Finding Words Associated with DIF: Predicting Differential Item Functioning using LLMs and Explainable AI0
Using agent-based models and EXplainable Artificial Intelligence (XAI) to simulate social behaviors and policy intervention scenarios: A case study of private well users in Ireland0
Coherent Local Explanations for Mathematical OptimizationCode0
A Wearable Device Dataset for Mental Health Assessment Using Laser Doppler Flowmetry and Fluorescence Spectroscopy SensorsCode1
Uncertainty Quantification of Wind Gust Predictions in the Northeast US: An Evidential Neural Network and Explainable Artificial Intelligence Approach0
Concept-Based Explainable Artificial Intelligence: Metrics and Benchmarks0
Towards Transparent and Accurate Diabetes Prediction Using Machine Learning and Explainable Artificial Intelligence0
Explainable Artificial Intelligence for identifying profitability predictors in Financial Statements0
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