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Statistical Confidence in Functional Correctness: An Approach for AI Product Functional Correctness Evaluation
AI systems pose challenges for quality assessment due to their probabilistic nature. This paper introduces the Statistical Confidence in Functional Correctness (SCFC) approach, a robust method that integrates statistical sampling and inference with capability analysis to evaluate AI functional correctness and quantify associated risks.