AWS Certified Cloud Practitioner

Explanation

Correct Answer: B - Use data-encryption, guardrails, and human review of AI-generated outputs

Why this is correct:

1. Data Encryption: Medical imaging data (including synthetic MRI data) is highly sensitive and falls under healthcare regulations like HIPAA. Encryption ensures data protection both at rest and in transit.

2. Guardrails: AWS provides AI service guardrails that help prevent harmful or inappropriate content generation, ensure data privacy, and maintain compliance with regulations.

3. Human Review: For medical applications, human oversight is critical to validate that synthetic data accurately represents real medical scenarios and doesn't introduce biases or errors that could impact patient care.

Why other options are incorrect:

• A) Disable logging to protect privacy: This is incorrect because logging is essential for auditing, compliance, and security monitoring. AWS provides mechanisms to protect privacy while maintaining necessary logs.

• C) Fully automate model approval with no oversight: This is dangerous for medical applications where human expertise is crucial to validate outputs and ensure patient safety.

• D) Publish all synthetic data publicly for open research: This violates patient privacy and healthcare regulations. Medical data, even synthetic, should be handled with strict privacy controls.

AWS Best Practices for Responsible AI:

1. Data Protection: Use AWS encryption services (KMS, S3 encryption) and access controls

2. Compliance: Follow healthcare regulations (HIPAA, GDPR) using AWS compliance programs

3. Transparency: Maintain audit trails and documentation

4. Human-in-the-loop: Critical review processes for sensitive applications

5. Bias Mitigation: Regular testing for fairness and accuracy in synthetic data generation