AI Data and Asset Management AAIR Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   What does data lineage primarily provide for an AI system?

   • AA backup and recovery plan for data
   • BA trace of data origin, transformations, and movement across the life cycle
   • CA classification of data sensitivity levels
   • DA record of who accessed the data and when
   Reveal Solution Discussion Select an answer first
2. 7foundation · easy

   What is the purpose of continuous monitoring in the AI data life cycle?

   • ATo replace the need for data quality checks
   • BTo eliminate the need for data governance
   • CTo automate all data processing tasks
   • DTo detect and respond to risks as they emerge throughout the data life cycle
   Reveal Solution Discussion Select an answer first
4. 8expert · hard

   A company is building an AI model using customer data that includes sensitive attributes such as health information. The data is subject to strict privacy regulations. The team wants to use the data for model training while minimizing privacy risks. Which approach is most effective?

   • AEncrypt the data and train the model on the encrypted data.
   • BRemove all sensitive attributes from the dataset.
   • CUse the raw data for training and rely on access controls to protect it.
   • DApply differential privacy to the training process to protect individual records.
   Reveal Solution Discussion Select an answer first
5. 9expert · hard

   A financial regulator is auditing an AI model used for loan approvals. The auditor asks for a complete record of how the training data was collected, transformed, and used. The company has a data lineage tool, but it only tracks the data from the source to the data warehouse, not the transformations applied during feature engineering. What is the most appropriate action?

   • AEnhance the data lineage tool to capture feature engineering transformations and document them for the audit.
   • BRecreate the feature engineering steps manually and provide a written description.
   • CProvide the auditor with the data lineage from the source to the warehouse, as it is sufficient.
   • DExplain that feature engineering is not part of data lineage.
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6. 10foundation · easy

   What is the goal of bias mitigation techniques in AI?

   • ATo ensure all data is anonymized
   • BTo reduce or eliminate unfair bias in AI outcomes
   • CTo eliminate all differences between groups in the data
   • DTo increase the accuracy of the model at any cost
   Reveal Solution Discussion Select an answer first