AI Associate Ethical Considerations of AI Practice Question
An AI system is used to approve loan applications. The model uses income, zip code, and credit score as features. What is a potential ethical concern?
⚠ Common exam trap
Salesforce often tests the misconception that bias is only introduced by explicitly using protected attributes, when in fact proxy features like zip code can cause discrimination even if race or gender is not directly used.
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
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Zip code may act as a proxy for race, leading to discrimination
Using zip code as a feature can introduce proxy discrimination. Zip codes are strongly correlated with race and socioeconomic status due to historical redlining and residential segregation. When the model learns patterns from zip code, it may inadvertently deny loans to applicants from certain racial or ethnic groups, violating fair lending laws and 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.
- ✓
Zip code may act as a proxy for race, leading to discrimination
Why this is correct
Using zip code can indirectly discriminate based on race or ethnicity.
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The model should be a black box to avoid bias
Why it's wrong here
Black-box models reduce accountability; transparency is needed.
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Credit scores are rarely accurate
Why it's wrong here
Credit scores are commonly used and generally accurate.
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Income is not a reliable predictor of repayment
Why it's wrong here
Income is a standard and legitimate factor in lending.
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