- A
Retain the features but monitor for disparate impact and ensure compliance with regulations.
Ethical AI allows use if monitored and regulated.
- B
Remove race and age features entirely to ensure fairness.
Why wrong: Age may be clinically relevant; removal could reduce accuracy unfairly.
- C
Replace age with an age group bucket to reduce granularity.
Why wrong: This does not address bias from race; still problematic.
- D
Use the model as is because predictions are accurate.
Why wrong: Accuracy does not justify ethical or legal risk.
Question 363 of 1,000
AI Associate Ethical Considerations of AI Practice Question
This AI Associate practice question tests your understanding of ethical considerations of ai. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A healthcare organization uses Einstein Discovery to predict patient readmission risk. The model uses protected attributes like race and age as features. Which action best aligns with Salesforce's ethical AI principles?
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
✓
Retain the features but monitor for disparate impact and ensure compliance with regulations.
Retaining protected attributes like race and age allows the model to leverage potentially legitimate medical correlations, but it requires ongoing monitoring for disparate impact to ensure fairness and compliance with regulations like HIPAA. This aligns with Salesforce's ethical AI principles of transparency, accountability, and fairness. Removing features entirely (Option B) may lose important medical context, while bucketing age (Option C) still risks bias and loss of granularity. Using the model as-is (Option D) ignores ethical responsibilities.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Retain the features but monitor for disparate impact and ensure compliance with regulations.
Why this is correct
Ethical AI allows use if monitored and regulated.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Remove race and age features entirely to ensure fairness.
Why it's wrong here
Age may be clinically relevant; removal could reduce accuracy unfairly.
- ✗
Replace age with an age group bucket to reduce granularity.
Why it's wrong here
This does not address bias from race; still problematic.
- ✗
Use the model as is because predictions are accurate.
Why it's wrong here
Accuracy does not justify ethical or legal risk.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the AI Associate exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which AI Associate exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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Ethical Considerations of AI — study guide chapter
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FAQ
Questions learners often ask
What does this AI Associate question test?
Ethical Considerations of AI — This question tests Ethical Considerations of AI — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Retain the features but monitor for disparate impact and ensure compliance with regulations. — Retaining protected attributes like race and age allows the model to leverage potentially legitimate medical correlations, but it requires ongoing monitoring for disparate impact to ensure fairness and compliance with regulations like HIPAA. This aligns with Salesforce's ethical AI principles of transparency, accountability, and fairness. Removing features entirely (Option B) may lose important medical context, while bucketing age (Option C) still risks bias and loss of granularity. Using the model as-is (Option D) ignores ethical responsibilities.
What should I do if I get this AI Associate question wrong?
Identify which AI Associate exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 22, 2026
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.
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