Explainability

Explainability refers to the degree to which the internal mechanisms of an artificial intelligence (AI) system or machine learning model can be understood by humans. It encompasses the transparency of algorithms, the interpretability of results, and the ability to communicate how decisions are made. High explainability enhances trust, accountability, and user confidence in AI applications, making it essential for sectors like finance, healthcare, and autonomous systems. As regulatory scrutiny increases, organizations prioritize explainability to ensure ethical AI deployment and compliance with standards.

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