AWS Certified AI Practitioner AIF-C01 Practice Question
A company is training a language model on Amazon SageMaker using sensitive customer data. To meet the privacy and security requirement of responsible AI, which practice should the company implement?
Use an F1 score threshold to tune overall model performance.
Encrypt the training data at rest with AWS Key Management Service (KMS) keys and ensure TLS encryption for data in transit.
Publish a model card describing the model's intended use and limitations.
Perform subgroup analysis to detect bias in model predictions.
Encrypting the dataset with AWS Key Management Service (KMS) keys protects it at rest, while enforcing TLS encryption secures data in transit. This approach directly addresses privacy and security requirements. Publishing a model card improves transparency, subgroup analysis addresses bias and fairness, and tuning by F1 score optimizes performance-none of these practices safeguard sensitive data.
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AWS Certified AI Practitioner AIF-C01
Guidelines for Responsible AI
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