Objective 1.1 Identify and Describe Common Terminology or Concepts Important to Data-Driven Technology Ethics CERTIFIED-ETHICAL-EMERGING-TECHNOLOGIST Practice Questions (Page 1)

Questions 1–5

1. 1expert · hard

   A multinational company operates in the EU and the US. They want to transfer customer data from the EU to the US for processing. The EU data protection authority has invalidated the Privacy Shield framework. Which approach is most appropriate for lawful data transfer?

   • ARely on the Privacy Shield framework because it was previously valid
   • BObtain explicit consent from each data subject for the transfer
   • CUse Standard Contractual Clauses (SCCs) and conduct a transfer impact assessment
   • DAnonymize the data before transfer to avoid GDPR obligations
   Reveal Solution Discussion Select an answer first
2. 2foundation · easy

   In the context of technology, what does 'ethics' primarily refer to?

   • AA legal framework that mandates specific technical standards
   • BA method for maximizing profit in technology companies
   • CA set of programming best practices for writing efficient code
   • DA set of moral principles that guide behavior and decision-making
   Reveal Solution Discussion Select an answer first
4. 3foundation · easy

   In the data science lifecycle, which step involves transforming raw data into a format that is suitable for analysis, such as handling missing values and correcting inconsistencies?

   • AData modeling
   • BData cleaning
   • CData collection
   • DData analysis
   Reveal Solution Discussion Select an answer first
5. 4expert · hard

   A healthcare research team is building a model to predict patient readmission risk. They have access to a large dataset of electronic health records. The dataset contains many missing values for income and education level. The team decides to fill missing income values with the median income of the patient's zip code. After training, the model performs well overall but shows poor performance for patients in low-income zip codes. Which combination of data science and ethical considerations best explains this outcome?

   • AThe imputation method introduced data bias by masking individual-level variation, and the team should evaluate subgroup performance
   • BThe team should collect more data from all zip codes to solve the problem
   • CThe model is overfitting to the training data, and the team should use a simpler model
   • DThe missing data is irrelevant because the model's overall accuracy is high
   Reveal Solution Discussion Select an answer first
6. 5foundation · easy

   Which type of evaluation metric is specifically used to assess whether a model's predictions are fair across different demographic groups?

   • AF1 score
   • BPrecision
   • CAccuracy
   • DFairness metrics
   Reveal Solution Discussion Select an answer first