Veracity in responsible AI focuses on the truthfulness, accuracy, and reliability of the data used to train a model and of the model's resulting outputs. Ensuring veracity involves validating, cleaning, and verifying data so that predictions are based on sound information. Robustness (consistent performance under varied or adversarial conditions), explainability (clarity of decision-making), and privacy (protection of personal data) are separate features that address different concerns.
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AWS Certified AI Practitioner AIF-C01
Guidelines for Responsible AI
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