Which of the following BEST describes the risk introduced when an organization uses an AI model's output as a feature input to a second AI model in a pipeline?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — d is correct because AI model pipelines introduce all three risks: error propagation (biases from model 1 become inputs to model 2, compounding errors), potential overfitting (model 2 may learn artifacts of model 1's outputs rather than true signal), and increased adversarial vulnerability (adversarial examples may transfer between models or be amplified through the pipeline). Each answer alone is partially correct, but D captures the comprehensive risk picture.
Full explanation below image
Full Explanation
D is correct because AI model pipelines introduce all three risks: error propagation (biases from model 1 become inputs to model 2, compounding errors), potential overfitting (model 2 may learn artifacts of model 1's outputs rather than true signal), and increased adversarial vulnerability (adversarial examples may transfer between models or be amplified through the pipeline). Each answer alone is partially correct, but D captures the comprehensive risk picture.