Which of the following metrics is NOT used to assess performance quality in AI?

Marketing effectiveness is not a metric used to assess performance quality in AI systems. Performance metrics for AI, especially in fields like dentistry, typically focus on how well the AI models can make accurate predictions or classifications based on data.

Robustness refers to the AI's ability to maintain performance when exposed to various conditions or inputs, which is crucial in ensuring reliability. Accuracy is a standard metric that measures how often the AI's predictions align with actual outcomes, reflecting its effectiveness in tasks like disease diagnosis or treatment planning. Sensitivity, also known as recall, measures the AI's ability to correctly identify positive instances within the data, which is particularly important in medical contexts where missing a diagnosis can have significant consequences.

In contrast, marketing effectiveness pertains to evaluating the impact of marketing strategies, which is outside the realm of technical AI performance metrics. Therefore, this choice stands out as it doesn't align with the core focus of performance evaluation typically associated with AI in practice.