Which of the following BEST describes the risk of model staleness in a deployed machine learning system?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — b is correct because model staleness (also called model drift) refers to the natural degradation of predictive accuracy over time as real-world conditions — customer behavior, market dynamics, language use — diverge from conditions captured in training data. A describes a supply chain or insider threat.
Full explanation below image
Full Explanation
B is correct because model staleness (also called model drift) refers to the natural degradation of predictive accuracy over time as real-world conditions — customer behavior, market dynamics, language use — diverge from conditions captured in training data. A describes a supply chain or insider threat. C describes model inversion or membership inference risk. D describes a compliance failure that may or may not relate to staleness.