Practice Test GeeksDSE - Data Science Practice Test
← All DSE Flashcard Decks

Ethical Considerations in AI Flashcards

7 cards from real DSE practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

Read the first 7 Ethical Considerations in AI flashcards as text

  1. A hiring algorithm trained on historical data consistently rates female applicants lower for engineering roles. This is best described as an example of:

    Answer: Representational bias

    Representational bias occurs when training data reflects historical inequalities, causing the model to perpetuate discrimination.

  2. Which principle in the EU AI Act classifies AI systems used in employment decisions as 'high-risk'?

    Answer: Proportionality of risk to impact on fundamental rights

    The EU AI Act classifies systems as high-risk based on their potential to adversely affect fundamental rights such as employment and livelihood.

  3. Differential privacy protects individual data by:

    Answer: Adding calibrated statistical noise to query outputs

    Differential privacy adds carefully calibrated noise so aggregate query results cannot reveal individual-level information.

  4. A data scientist discovers a production model produces biased outcomes but faces pressure from management to delay fixes. The most ethical course of action is to:

    Answer: Document findings and escalate through formal channels

    Documenting and escalating ensures accountability, creates an audit trail, and upholds professional responsibility.

  5. What does 'explainability' mean in the context of AI ethics?

    Answer: Providing understandable reasons for a model's specific predictions

    Explainability means stakeholders can understand why a model produced a particular output, enabling scrutiny and trust.

  6. Which technique is specifically designed to identify which features most influenced a model prediction for a single instance?

    Answer: SHAP (SHapley Additive exPlanations)

    SHAP assigns each feature a contribution value for a specific prediction based on game-theoretic Shapley values.

  7. A company uses a facial recognition model that has a 1% error rate for light-skinned males but a 35% error rate for dark-skinned females. This performance gap is primarily a concern under which ethical principle?

    Answer: Fairness and non-discrimination

    Disparate error rates across demographic groups violate fairness and non-discrimination principles central to AI ethics.