Model trust is the confidence stakeholders place in an AI system’s reliability, fairness, and transparency. It’s built through rigorous validation, explainable outputs, and continuous monitoring. Used by data scientists to refine algorithms, it benefits businesses by reducing compliance risks and end-users by ensuring safe, unbiased decisions. Ultimately, trust bridges the gap between technical performance and real-world adoption.
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