Objective 1.1 Identify and Describe Common Terminology or Concepts Important to Data-Driven Technology Ethics CERTIFIED-ETHICAL-EMERGING-TECHNOLOGIST Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   Which legal concept protects creations of the mind, such as inventions, literary works, and software code, and is relevant to data-driven technologies?

   • AConsent
   • BIntellectual property
   • CLiability
   • DData sovereignty
   Reveal Solution Discussion Select an answer first
2. 7application · medium

   A startup develops an AI-powered chatbot that provides legal advice. The chatbot sometimes gives incorrect advice, and a user relies on it and suffers financial loss. Which legal and ethical concept is most relevant to this situation?

   • AData minimization in the chatbot's training data
   • BLiability for the chatbot's outputs
   • CIntellectual property rights in the chatbot's code
   • DThe right to be forgotten for the user's chat history
   Reveal Solution Discussion Select an answer first
4. 8application · medium

   A social media platform introduces an NLP-based feature that automatically summarizes news articles. Users report that the summaries sometimes reflect the political bias of the training data. The product manager wants to address this ethically. Which action is most appropriate?

   • ADisclose to users that summaries are AI-generated and may reflect biases in the training data
   • BKeep the feature as-is because NLP models are objective
   • COnly show summaries to users who opt in to AI-generated content
   • DRemove the feature entirely to avoid any potential bias
   Reveal Solution Discussion Select an answer first
5. 9application · medium

   A European e-commerce company wants to build a recommendation engine. They have collected customer purchase history and browsing behavior. To comply with GDPR, they plan to anonymize the data before using it for model training. However, the legal team warns that the anonymization process must be robust. Which combination of practices best supports lawful and ethical use of this data?

   • AObtain broad consent once for all future uses of the data
   • BCollect only the data fields strictly needed for the recommendation model and apply a formally validated anonymization method
   • CStore the raw data indefinitely in case the model needs retraining
   • DApply a simple pseudonymization technique and document it as fully anonymous
   Reveal Solution Discussion Select an answer first
6. 10application · medium

   A bank develops a machine learning model to approve loan applications. The model is designed to maximize overall approval accuracy. The bank's compliance team reviews the model and finds that the false positive rate (approving a loan that defaults) is much higher for applicants under 30 than for older applicants. Which evaluation approach would best help the bank understand and address this issue?

   • ACompute and compare fairness metrics such as equalized odds across age groups
   • BReport only the overall F1 score to senior management
   • CIncrease the model's overall accuracy threshold to reduce all errors uniformly
   • DRemove the age feature from the model and assume the problem is solved
   Reveal Solution Discussion Select an answer first