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 company uses Einstein Analytics to predict employee performance and identifies low-performing employees with high confidence. What is a potential ethical concern?
Invasion of employee privacy.
Predicting performance often uses personal data, raising privacy concerns.
High computational cost.
Why wrong: Cost is not an ethical issue.
Difficulty in interpreting the model.
Why wrong: Interpretability is important but privacy is more direct.
Overfitting on historical data.
Why wrong: Overfitting is technical, not ethical.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Invasion of employee privacy.
Einstein Analytics uses machine learning models to analyze employee data and predict performance. Identifying low-performing employees with high confidence raises ethical concerns about invasion of privacy because the model may rely on sensitive personal data (e.g., communication patterns, work hours, or behavioral metrics) without explicit employee consent or transparency. This violates principles of data minimization and informed consent, which are core to ethical AI frameworks.
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.
Invasion of employee privacy.
Why this is correct
Predicting performance often uses personal data, raising privacy concerns.
Related concept
Read the scenario before looking for a memorised answer.
High computational cost.
Why it's wrong here
Cost is not an ethical issue.
Difficulty in interpreting the model.
Why it's wrong here
Interpretability is important but privacy is more direct.
Overfitting on historical data.
Why it's wrong here
Overfitting is technical, not ethical.
Common exam traps
Salesforce often tests the distinction between ethical concerns (privacy, bias, transparency) and technical issues (cost, performance, overfitting), so the trap here is that candidates may confuse a model's high confidence with accuracy or fairness, overlooking that the ethical problem lies in the unauthorized use of personal data to make high-stakes predictions.
Detailed technical explanation
Einstein Analytics often ingests data from Salesforce CRM, email, calendar, and collaboration tools to build predictive models. Under the hood, it may use feature engineering on metadata like email response times or meeting attendance, which can infer sensitive attributes (e.g., engagement, stress levels). In a real-world scenario, if an employer uses such predictions to make termination decisions without employee awareness, it could violate GDPR or CCPA regulations, which require explicit consent for processing personal data and the right to explanation for automated decisions.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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What to study next
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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: Invasion of employee privacy. — Einstein Analytics uses machine learning models to analyze employee data and predict performance. Identifying low-performing employees with high confidence raises ethical concerns about invasion of privacy because the model may rely on sensitive personal data (e.g., communication patterns, work hours, or behavioral metrics) without explicit employee consent or transparency. This violates principles of data minimization and informed consent, which are core to ethical AI frameworks.
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
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