AIF-C01 · Question #67
An AI practitioner trained a custom model on Amazon Bedrock by using a training dataset that contains confidential data. The AI practitioner wants to ensure that the custom model does not generate…
The correct answer is A. Delete the custom model. Remove the confidential data from the training dataset. Retrain the. When a model is trained on a dataset containing confidential or sensitive data, the model may inadvertently learn patterns from this data, which could then be reflected in its inference responses. To ensure that a model does not generate responses based on confidential data…
Question
An AI practitioner trained a custom model on Amazon Bedrock by using a training dataset that contains confidential data. The AI practitioner wants to ensure that the custom model does not generate inference responses based on confidential data. How should the AI practitioner prevent responses based on confidential data?
Options
- ADelete the custom model. Remove the confidential data from the training dataset. Retrain the
- BMask the confidential data in the inference responses by using dynamic data masking.
- CEncrypt the confidential data in the inference responses by using Amazon SageMaker.
- DEncrypt the confidential data in the custom model by using AWS Key Management Service (AWS
How the community answered
(26 responses)- A69% (18)
- B4% (1)
- C12% (3)
- D15% (4)
Explanation
When a model is trained on a dataset containing confidential or sensitive data, the model may inadvertently learn patterns from this data, which could then be reflected in its inference responses. To ensure that a model does not generate responses based on confidential data, the most effective approach is to remove the confidential data from the training dataset and then retrain the model.
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