AI Associate Ethical Considerations of AI Practice Question
A company's Einstein Discovery model for customer lifetime value shows a significant correlation between predicted value and customer's postal code. The company is concerned about ethical implications. What is the most appropriate response?
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
✓
Investigate whether postal code is a proxy for protected attributes and, if so, consider retraining the model without it or with fairness constraints
(Investigate whether postal code is a proxy for protected attributes and, if so, consider retraining the model without it or with fairness constraints) is correct because postal code can be a proxy for race or income. Option A (removing postal code outright) may not be straightforward. Option C (ignoring correlation as coincidental) is unethical. Option D (adding more demographic data) could increase bias.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Remove the postal code field from the model immediately
Why it's wrong here
Removing may not be optimal if the model relies on it for accuracy; need to handle proxy variables carefully.
- ✓
Investigate whether postal code is a proxy for protected attributes and, if so, consider retraining the model without it or with fairness constraints
Why this is correct
This approach addresses the ethical concern while preserving model utility.
- ✗
Add more demographic data to the model to improve its accuracy
Why it's wrong here
Adding more demographic data could exacerbate bias.
- ✗
Ignore the correlation since the model is predicting business value, not demographic attributes
Why it's wrong here
Ignoring proxy bias can lead to discriminatory outcomes.
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