Question 317 of 506

Ethical Considerations of AI →hardMultiple SelectObjective-mapped

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.

Exhibit

{
  "model_id": "AI-123",
  "accuracy": 0.95,
  "fairness_metrics": {
    "demographic_parity_difference": 0.12,
    "equal_opportunity_difference": 0.08,
    "disparate_impact": 0.85
  },
  "approved_by": "john.doe@example.com",
  "audit_trail": ["2025-01-15 initial training", "2025-02-01 bias detected", "2025-02-10 retrained"]
}

Refer to the exhibit. A Salesforce AI Associate is reviewing the AI model evaluation data. Which TWO ethical concerns should the associate identify?

Question 1hardmulti select

Full question →

Exhibit

{
  "model_id": "AI-123",
  "accuracy": 0.95,
  "fairness_metrics": {
    "demographic_parity_difference": 0.12,
    "equal_opportunity_difference": 0.08,
    "disparate_impact": 0.85
  },
  "approved_by": "john.doe@example.com",
  "audit_trail": ["2025-01-15 initial training", "2025-02-01 bias detected", "2025-02-10 retrained"]
}

A
The demographic parity difference of 0.12 indicates potential bias against a protected group.
A difference of 0.12 is often considered above acceptable limits, raising fairness concerns.
B
The model accuracy of 0.95 is too low to be deployed in production.
Why wrong: An accuracy of 0.95 is generally high; there is no ethical concern solely based on this value.
C
The model was approved by a single individual, which violates the principle of diversity in AI oversight.
Why wrong: While diverse oversight is beneficial, approval by one person is not inherently unethical without more context.
D
The disparate impact ratio of 0.85 falls below the acceptable threshold of 0.80, indicating adverse impact.
Why wrong: The disparate impact ratio of 0.85 is above 0.80, so it does not indicate adverse impact under the four-fifths rule.
E
The audit trail shows that bias was detected but does not indicate what remedial actions were taken.
Lack of documentation on remediation steps raises transparency and accountability concerns.

Full breakdown with real-world context →

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

✓

The demographic parity difference of 0.12 indicates potential bias against a protected group.

Option B is correct because a demographic parity difference of 0.12 exceeds commonly accepted thresholds (e.g., 0.1), indicating potential bias. Option D is correct because the audit trail shows bias was detected but does not document specific remedial actions, which is a transparency concern. Option A is incorrect because 0.95 accuracy is typically acceptable. Option C is incorrect because a disparate impact of 0.85 is above the 0.80 threshold, so it does not indicate adverse impact. Option E is incorrect while having a single approver may be noted, but it is not explicitly an ethical concern without context.

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.

✓
The demographic parity difference of 0.12 indicates potential bias against a protected group.
Why this is correct
A difference of 0.12 is often considered above acceptable limits, raising fairness concerns.
Related concept
Read the scenario before looking for a memorised answer.
✗
The model accuracy of 0.95 is too low to be deployed in production.
Why it's wrong here
An accuracy of 0.95 is generally high; there is no ethical concern solely based on this value.
✗
The model was approved by a single individual, which violates the principle of diversity in AI oversight.
Why it's wrong here
While diverse oversight is beneficial, approval by one person is not inherently unethical without more context.
✗
The disparate impact ratio of 0.85 falls below the acceptable threshold of 0.80, indicating adverse impact.
Why it's wrong here
The disparate impact ratio of 0.85 is above 0.80, so it does not indicate adverse impact under the four-fifths rule.
✓
The audit trail shows that bias was detected but does not indicate what remedial actions were taken.
Why this is correct
Lack of documentation on remediation steps raises transparency and accountability concerns.
Related concept
Read the scenario before looking for a memorised answer.

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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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: The demographic parity difference of 0.12 indicates potential bias against a protected group. — Option B is correct because a demographic parity difference of 0.12 exceeds commonly accepted thresholds (e.g., 0.1), indicating potential bias. Option D is correct because the audit trail shows bias was detected but does not document specific remedial actions, which is a transparency concern. Option A is incorrect because 0.95 accuracy is typically acceptable. Option C is incorrect because a disparate impact of 0.85 is above the 0.80 threshold, so it does not indicate adverse impact. Option E is incorrect while having a single approver may be noted, but it is not explicitly an ethical concern without context.

What should I do if I get this AI Associate question wrong?

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 23, 2026

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