Explainability is the property of a model that allows humans to understand why the model produced a particular output. It focuses on revealing the factors or reasoning that led to each prediction so stakeholders can trust, debug, and govern the system. Balanced data relates to fairness, robustness concerns resistance to adversarial inputs, and low resource consumption relates to sustainability, not explainability.
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Guidelines for Responsible AI
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