Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead

Citation edge evidence

Each row is directed from the citing work to the cited work. Source status remains readable without the interactive graph.

• Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…→Stop explaining black box machine learning models for high stakes decisions and use inter…Legacy edge — source detail unavailable
• On the Opportunities and Risks of Foundation Models→Stop explaining black box machine learning models for high stakes decisions and use inter…Legacy edge — source detail unavailable
• Definitions, methods, and applications in interpretable machine learning→Stop explaining black box machine learning models for high stakes decisions and use inter…Legacy edge — source detail unavailable
• Artificial intelligence in digital pathology — new tools for diagnosis and precision onco…→Stop explaining black box machine learning models for high stakes decisions and use inter…Legacy edge — source detail unavailable
• Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→Stop explaining black box machine learning models for high stakes decisions and use inter…Legacy edge — source detail unavailable
• The false hope of current approaches to explainable artificial intelligence in health care→Stop explaining black box machine learning models for high stakes decisions and use inter…Legacy edge — source detail unavailable
• Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications→Stop explaining black box machine learning models for high stakes decisions and use inter…Legacy edge — source detail unavailable
• Stop explaining black box machine learning models for high stakes decisions and use inter…→Classification and Regression Trees.Legacy edge — source detail unavailable
• Stop explaining black box machine learning models for high stakes decisions and use inter…→The magical number seven, plus or minus two: Some limits on our capacity for processing i…Legacy edge — source detail unavailable
• Stop explaining black box machine learning models for high stakes decisions and use inter…→Domain-Adversarial Training of Neural NetworksLegacy edge — source detail unavailable
• Stop explaining black box machine learning models for high stakes decisions and use inter…→Definitions, methods, and applications in interpretable machine learningLegacy edge — source detail unavailable
• Definitions, methods, and applications in interpretable machine learning→Classification and Regression Trees.Legacy edge — source detail unavailable
• Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…→Definitions, methods, and applications in interpretable machine learningLegacy edge — source detail unavailable
• On the Opportunities and Risks of Foundation Models→Artificial intelligence in digital pathology — new tools for diagnosis and precision onco…Legacy edge — source detail unavailable
• Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→Definitions, methods, and applications in interpretable machine learningLegacy edge — source detail unavailable
• Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe…Legacy edge — source detail unavailable
• Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…→The false hope of current approaches to explainable artificial intelligence in health careLegacy edge — source detail unavailable