AWS AI Security and Governance Quiz

1. Which AWS feature enables automated compliance scanning of AI resources?

AWS Config

Amazon GuardDuty

AWS Backup

AWS Lambda

2. Which principle ensures AI systems can be understood by stakeholders and regulators?

Opacity

Transparency

Complexity

Automation

3. What is the role of data retention policies in AI governance?

To maximize storage capacity

To ensure compliance and delete data when no longer needed

To improve model accuracy

To eliminate the need for backups

4. How does Amazon SageMaker Clarify assist with AI governance?

By automatically selecting optimal hyperparameters

By detecting bias and explaining model predictions

By encrypting all model data

By reducing training costs

5. What does encryption at rest protect in AI workloads?

Data during network transmission

Data stored in databases and S3

Model inference speed

User interface interactions

6. Which practice helps ensure fairness across different demographic groups in AI models?

Using only majority group data

Conducting fairness audits and testing across groups

Ignoring demographic variables entirely

Increasing model complexity

7. What is the purpose of model versioning in AI governance?

To increase model size

To track changes and enable rollback if needed

To reduce training time

To eliminate model monitoring

8. Which AWS service helps detect sensitive data in datasets before training?

Amazon Macie

AWS Glue

Amazon EMR

AWS Data Exchange

9. How can adversarial attacks affect AI model security?

They improve model accuracy

They manipulate inputs to cause incorrect predictions

They reduce inference costs

They eliminate the need for monitoring

10. What does GDPR's 'right to explanation' require for AI systems?

Explaining model architecture to end users

Providing interpretable decisions for automated processing

Publishing all training data

Removing all personal data immediately

11. Which AWS service provides centralized management of encryption keys for AI models and data?

AWS Key Management Service (KMS)

AWS CloudTrail

AWS Config

AWS Identity and Access Management (IAM)

12. What is data lineage in the context of AI governance?

The chronological order of model predictions

Tracking the origin, movement, and transformation of data

The process of data encryption

The number of data sources used

13. How does AWS IAM help secure AI workloads?

By encrypting data in transit

By managing user access and permissions to AI services

By monitoring model performance

By automatically detecting bias

14. Which principle is central to responsible AI governance?

Maximizing accuracy at any cost

Transparency, fairness, accountability, and security

Deploying models as quickly as possible

Avoiding all regulatory requirements

15. What is the role of Amazon SageMaker Model Monitor?

To create training datasets

To detect data quality issues and model performance degradation

To encrypt model artifacts

To scale inference endpoints automatically

16. Bias in AI models can lead to unfair outcomes. Which practice best mitigates bias during model development?

Using only historical data without review

Analyzing training data for bias and using diverse datasets

Increasing model complexity

Removing all features related to demographics

17. Which AWS service is used to track API calls and user activities for audit compliance?

AWS CloudWatch

AWS CloudTrail

AWS VPC Flow Logs

AWS Config

18. What does model explainability refer to in AI governance?

The speed at which a model makes predictions

The ability to understand and interpret model decisions

The number of features used in the model

The cost of deploying the model

19. Which compliance framework is most commonly used for AI systems handling sensitive data in healthcare?

GDPR

HIPAA

SOC 2

ISO 27001

20. What is the primary purpose of model monitoring in AI governance?

To reduce inference latency

To detect model drift and performance degradation

To increase model complexity

To eliminate the need for retraining

AWS AI Practitioner AI Security and Governance Quiz

1. Which AWS feature enables automated compliance scanning of AI resources?

2.

What first name or nickname would you like us to use?

2. Which principle ensures AI systems can be understood by stakeholders and regulators?

3. What is the role of data retention policies in AI governance?

4. How does Amazon SageMaker Clarify assist with AI governance?

5. What does encryption at rest protect in AI workloads?

6. Which practice helps ensure fairness across different demographic groups in AI models?

7. What is the purpose of model versioning in AI governance?

8. Which AWS service helps detect sensitive data in datasets before training?

9. How can adversarial attacks affect AI model security?

10. What does GDPR's 'right to explanation' require for AI systems?

11. Which AWS service provides centralized management of encryption keys for AI models and data?

12. What is data lineage in the context of AI governance?

13. How does AWS IAM help secure AI workloads?

14. Which principle is central to responsible AI governance?

15. What is the role of Amazon SageMaker Model Monitor?

16. Bias in AI models can lead to unfair outcomes. Which practice best mitigates bias during model development?

17. Which AWS service is used to track API calls and user activities for audit compliance?

18. What does model explainability refer to in AI governance?

19. Which compliance framework is most commonly used for AI systems handling sensitive data in healthcare?

20. What is the primary purpose of model monitoring in AI governance?