- A
Fairness
Why wrong: Fairness is about ensuring AI systems do not discriminate against groups, not directly about data security.
- B
Transparency
Why wrong: Transparency is about making AI systems understandable and explainable, not specifically about data protection.
- C
Privacy and security
Correct. This principle emphasizes protecting data and ensuring secure access, which directly addresses the hospital's requirement.
- D
Inclusiveness
Why wrong: Inclusiveness focuses on designing AI to empower everyone and accommodate diverse needs, not data security.
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. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 hospital uses an AI system to analyze patient health records for research. The hospital must ensure that all patient data is stored securely and only authorized personnel can access it. Which Microsoft responsible AI principle is most directly relevant?
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 and security
Option C is correct because the scenario explicitly focuses on secure storage and access control of patient data, which directly aligns with Microsoft's responsible AI principle of Privacy and security. This principle ensures that data is protected against unauthorized access and breaches, often implemented through encryption (e.g., AES-256 for data at rest, TLS 1.2+ for data in transit) and role-based access control (RBAC) in Azure services like Azure SQL Database or Azure Blob Storage.
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 ensuring AI systems do not discriminate against groups, not directly about data security.
- ✗
Transparency
Why it's wrong here
Transparency is about making AI systems understandable and explainable, not specifically about data protection.
- ✓
Privacy and security
Why this is correct
Correct. This principle emphasizes protecting data and ensuring secure access, which directly addresses the hospital's requirement.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Inclusiveness
Why it's wrong here
Inclusiveness focuses on designing AI to empower everyone and accommodate diverse needs, not data security.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse 'privacy and security' with 'transparency' because both involve data handling, but transparency is about model explainability, not data protection.
Detailed technical explanation
How to think about this question
Under the hood, Azure implements Privacy and security through Azure Policy, Azure Active Directory (now Microsoft Entra ID) for authentication, and Azure Key Vault for managing encryption keys. In a real-world hospital scenario, this principle would require compliance with HIPAA or GDPR, using Azure's built-in compliance offerings like Azure Blueprints to enforce data residency and access logging via Azure Monitor.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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 and security — Option C is correct because the scenario explicitly focuses on secure storage and access control of patient data, which directly aligns with Microsoft's responsible AI principle of Privacy and security. This principle ensures that data is protected against unauthorized access and breaches, often implemented through encryption (e.g., AES-256 for data at rest, TLS 1.2+ for data in transit) and role-based access control (RBAC) in Azure services like Azure SQL Database or Azure Blob Storage.
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.
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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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