A development team wants to confirm that their machine-learning model continues to produce accurate results when the input data contain slight errors or unexpected variations. Which responsible AI feature are they primarily evaluating?
Fairness
Inclusivity
Veracity
Robustness
The team is assessing the model's robustness. Robustness refers to an AI system's ability to maintain correct performance when facing noisy, perturbed, or previously unseen inputs. Fairness focuses on equitable treatment of different user groups, inclusivity on ensuring diverse populations are represented and served, and veracity on the factual accuracy or truthfulness of the model's outputs. Therefore, robustness is the only feature that addresses resilience to input variations.
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