Quick Answer
The answer is all of the above because each listed risk—over-reliance on the model, privacy violation, and underutilization of human judgment—represents a distinct ethical risk of AI in HR when an AI model predicts employee performance. Over-reliance occurs when the HR team treats the model’s output as infallible, automating decisions without human oversight, while privacy violation arises if sensitive employee data is mishandled during training or inference. Underutilization of human judgment ignores contextual factors like team dynamics or personal circumstances that the model cannot capture. On the Salesforce AI Associate exam, this question tests your understanding of comprehensive ethical risks rather than isolated concerns; a common trap is selecting only one risk because it seems most obvious. Remember the mnemonic “OPU” for Over-reliance, Privacy, and Underutilization—if any one is missing, the answer is incomplete.
This AI Associate practice question tests your understanding of ethical considerations of ai. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
An AI model predicts employee performance. The HR team uses it to identify high-potential employees. What is a potential ethical risk?
Over-reliance on the model
Why wrong: This is a risk, but not the only one.
Privacy violation
Why wrong: Privacy is a risk but not the only one.
Underutilization of human judgment
Why wrong: Also a risk, but the question asks for the best answer.
All of the above
Correct. All listed risks are potential ethical concerns.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
All of the above
Option D is correct because all three listed risks—over-reliance on the model, privacy violation, and underutilization of human judgment—are potential ethical risks when an AI model predicts employee performance. Over-reliance can lead to automated decisions without human oversight, privacy violation may occur if sensitive employee data is mishandled, and underutilization of human judgment ignores contextual factors that the model cannot capture. Together, these represent a comprehensive set of ethical concerns in AI-driven HR practices.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Over-reliance on the model
Why it's wrong here
This is a risk, but not the only one.
Privacy violation
Why it's wrong here
Privacy is a risk but not the only one.
Underutilization of human judgment
Why it's wrong here
Also a risk, but the question asks for the best answer.
All of the above
Why this is correct
Correct. All listed risks are potential ethical concerns.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Salesforce often tests the 'all of the above' trap where candidates think only one or two risks apply, but the question explicitly lists multiple interconnected ethical concerns that collectively form the correct answer.
Detailed technical explanation
Under the hood, AI models for employee performance often use supervised learning on historical HR data, which can encode biases (e.g., gender, tenure) and require careful feature engineering to avoid proxy discrimination. A real-world scenario is Amazon's scrapped hiring tool that penalized resumes containing the word 'women's,' illustrating how model outputs can perpetuate systemic bias if human judgment is sidelined. The ethical risk is amplified when the model's confidence scores are used as sole decision criteria without explainability or fairness audits.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Ethical Considerations of AI — This question tests Ethical Considerations of AI — Read the scenario before looking for a memorised answer..
The correct answer is: All of the above — Option D is correct because all three listed risks—over-reliance on the model, privacy violation, and underutilization of human judgment—are potential ethical risks when an AI model predicts employee performance. Over-reliance can lead to automated decisions without human oversight, privacy violation may occur if sensitive employee data is mishandled, and underutilization of human judgment ignores contextual factors that the model cannot capture. Together, these represent a comprehensive set of ethical concerns in AI-driven HR practices.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 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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