- A
Fairness
Why wrong: Fairness is about avoiding bias and ensuring equitable treatment across groups. The scenario does not describe bias or discrimination; it describes a lack of consent and transparency.
- B
Privacy & Security
The scenario involves collecting personal data (keystrokes and mouse movements) without employee knowledge or consent. This directly violates the Privacy & Security principle, which requires that data be collected transparently and with consent.
- C
Reliability & Safety
Why wrong: Reliability & Safety ensures that AI systems operate correctly and safely. The scenario does not mention system failures or unsafe behavior; it focuses on unauthorized data collection.
- D
Inclusiveness
Why wrong: Inclusiveness aims to empower everyone and ensure AI systems are accessible to diverse users. The scenario does not relate to accessibility or exclusion of groups.
Quick Answer
The answer is the Privacy & Security principle. This is correct because the scenario describes an AI system collecting keystrokes and mouse movements—both forms of personal data—without employee knowledge or consent, which directly violates the requirement that individuals have control over their personal information and that data collection must be transparent. On the Microsoft Azure AI Fundamentals AI-900 exam, this question tests your understanding of how responsible AI principles apply to real-world monitoring scenarios; a common trap is confusing this with the Fairness principle, but remember that consent and data control are the core of Privacy & Security. A useful memory tip is to link "monitoring without consent" to "privacy breach"—if data is collected secretly, it’s a privacy and security violation, not a fairness issue.
AI-900 Practice Question: Describe Artificial Intelligence workloads and considerations
This AI-900 practice question tests your understanding of describe artificial intelligence workloads and considerations. 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 implements an AI system to monitor employee productivity by tracking keystrokes and mouse movements. Employees are not informed that this monitoring is taking place, nor did they consent to it. Which Microsoft responsible AI principle is most directly violated?
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
Privacy & Security
The scenario describes monitoring employee keystrokes and mouse movements without their knowledge or consent. This directly violates the Privacy & Security principle, which requires that individuals have control over their personal data and that data collection is transparent and consensual. Microsoft's responsible AI framework mandates that AI systems must respect privacy and obtain informed consent before collecting or using personal data.
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.
- ✗
Fairness
Why it's wrong here
Fairness is about avoiding bias and ensuring equitable treatment across groups. The scenario does not describe bias or discrimination; it describes a lack of consent and transparency.
- ✓
Privacy & Security
Why this is correct
The scenario involves collecting personal data (keystrokes and mouse movements) without employee knowledge or consent. This directly violates the Privacy & Security principle, which requires that data be collected transparently and with consent.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Reliability & Safety
Why it's wrong here
Reliability & Safety ensures that AI systems operate correctly and safely. The scenario does not mention system failures or unsafe behavior; it focuses on unauthorized data collection.
- ✗
Inclusiveness
Why it's wrong here
Inclusiveness aims to empower everyone and ensure AI systems are accessible to diverse users. The scenario does not relate to accessibility or exclusion of groups.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse 'Privacy & Security' with 'Fairness' because they think monitoring without consent is 'unfair,' but the specific principle violated is about data control and transparency, not bias or discrimination.
Trap categories for this question
Scenario analysis trap
Fairness is about avoiding bias and ensuring equitable treatment across groups. The scenario does not describe bias or discrimination; it describes a lack of consent and transparency.
Detailed technical explanation
How to think about this question
Under the hood, the Privacy & Security principle aligns with regulations like GDPR and the California Consumer Privacy Act (CCPA), which require explicit opt-in consent for data collection, especially for biometric or behavioral data such as keystroke dynamics. In practice, even if the monitoring software is technically capable of logging input events via hooks like SetWindowsHookEx (on Windows), deploying it without disclosure violates the principle of data minimization and purpose limitation. A real-world scenario is the 2021 case of a company using employee monitoring software that was fined under GDPR for failing to inform workers about the extent of surveillance.
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.
TExam Day Tips
- 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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
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FAQ
Questions learners often ask
What does this AI-900 question test?
Describe Artificial Intelligence workloads and considerations — This question tests Describe Artificial Intelligence workloads and considerations — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Privacy & Security — The scenario describes monitoring employee keystrokes and mouse movements without their knowledge or consent. This directly violates the Privacy & Security principle, which requires that individuals have control over their personal data and that data collection is transparent and consensual. Microsoft's responsible AI framework mandates that AI systems must respect privacy and obtain informed consent before collecting or using personal data.
What should I do if I get this AI-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jun 11, 2026
This AI-900 practice question is part of Courseiva's free Microsoft 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-900 exam.
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