Transparency
Being open about how an AI system works, its data, and its limitations.
Transparency means openly disclosing how an AI system makes decisions, what data it was trained on, its intended uses, and known limitations, so users and regulators can judge whether to rely on it. On AIF-C01, Amazon SageMaker Model Cards are the primary mechanism, capturing training details, intended uses, evaluation results, and ethical considerations in a standardized document. Do not confuse transparency with explainability: explainability interprets a specific prediction (why this output?), while transparency is the broader practice of disclosing system design and governance.
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