AI Associate Data for AI Practice Question
A bank uses Einstein Discovery to generate insights about loan approval decisions. After deployment, they notice the model denies loans to a higher percentage of applicants from a certain postal code. Which action should be taken to ensure responsible AI?
⚠ Common exam trap
Salesforce often tests the misconception that removing a sensitive feature (like postal code) automatically eliminates bias, when in reality proxy features and correlated variables can still cause unfair outcomes.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Audit model outcomes for fairness across demographic groups and retrain if needed
Responsible AI requires auditing model outcomes for fairness across demographic groups, even when the disparity correlates with a non-protected attribute like postal code. In Einstein Discovery, postal code can act as a proxy for protected attributes such as race or socioeconomic status, and ignoring this could lead to discriminatory lending practices. Auditing allows the team to detect and mitigate bias, and retraining with fairness constraints ensures the model aligns with ethical AI principles.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Ignore the discrepancy because postal code is not a protected attribute
Why it's wrong here
Postal code can be a proxy for race/income; ignoring is risky.
- ✗
Retrain the model using only recent loan data
Why it's wrong here
Recent data may have same bias.
- ✓
Audit model outcomes for fairness across demographic groups and retrain if needed
Why this is correct
Bias audit and mitigation is a standard responsible AI practice.
- ✗
Remove the postal code field from the model
Why it's wrong here
Other features may correlate with postal code, so bias may persist.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI Associate practice question is part of Courseiva's free Salesforce certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI Associate exam.