AI-900 Practice Question: Describe Artificial Intelligence workloads and considerations
A healthcare organization plans to use AI to analyze patient records for medical research. They must ensure that patient data is protected from unauthorized access during storage and processing. Which Microsoft responsible AI principle is most directly relevant to this requirement?
⚠ Common exam trap
Test-takers frequently confuse the Privacy and security principle with Reliability and safety, because both involve 'protection'—but reliability protects against system failures, not unauthorized data access.
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
The requirement to protect patient data from unauthorized access during storage and processing directly aligns with the Privacy and security principle. This principle mandates that AI systems implement robust data protection mechanisms, such as encryption at rest (e.g., AES-256) and in transit (e.g., TLS 1.2/1.3), access controls (e.g., Azure RBAC), and compliance with regulations like HIPAA. It ensures that sensitive healthcare data remains confidential and secure throughout its lifecycle.
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 as an AI principle focuses on eliminating biased outcomes and ensuring equitable treatment across demographic groups such as race, gender, or age. Although this is crucial in healthcare analytics, it does not govern how patient data is stored, accessed, or protected. The requirement to analyze patient data securely is a data protection concern, not a bias-prevention concern, so Fairness is not the correct principle.
- ✓
Privacy and security
Why this is correct
Privacy and security is the responsible AI principle that explicitly covers controlling access to sensitive information and safeguarding it from unauthorized use or breaches. When analyzing patient data, this principle mandates encryption, role-based access controls, data minimization, and compliance with regulations like HIPAA or GDPR. It also gives patients rights over their own data, which directly matches the requirement stated in the question.
- ✗
Inclusiveness
Why it's wrong here
Inclusiveness means designing AI systems that empower and are accessible to everyone, including people with disabilities or varied cultural and linguistic backgrounds. For patient data analysis, inclusiveness might dictate accessible interfaces or representative datasets, but it does not address confidentiality or protection of the underlying medical records. The concern about data protection belongs to a different pillar, so Inclusiveness is not the correct answer.
- ✗
Reliability and safety
Why it's wrong here
Reliability and safety ensures that AI systems perform consistently, avoid harmful errors, and remain robust under real-world conditions. In healthcare, this principle would govern clinical decision-support accuracy and fail-safe mechanisms, but it does not define how to protect patient data from unauthorized access or disclosure. Secure data handling is a separate concern, making Reliability and safety incorrect for this specific requirement.
Quick reference
Symmetric Encryption Algorithm Comparison
| Algorithm | Key Size | Block Size | Status | Notes |
|---|---|---|---|---|
| AES-128 | 128-bit | 128-bit | Current standard | NIST approved; WPA3, TLS |
| AES-256 | 256-bit | 128-bit | Current standard | Preferred for sensitive / govt data |
| 3DES | 112-bit effective | 64-bit | Deprecated (2023) | Replaced by AES |
| DES | 56-bit | 64-bit | Broken | Cracked in < 24 h; never deploy |
| ChaCha20 | 256-bit | Stream cipher | Current | TLS 1.3, WireGuard |
Go deeper
Related to this question
Learn chapter
Responsible AI Principles
Key term
Responsible AI
A framework of ethical principles and practices that ensure artificial intelligence systems are developed and deployed in a transparent, fair, accountable, and safe manner.
Key term
Privacy and security
Privacy and security refer to the practices and technologies used to protect sensitive data from unauthorized access while ensuring individuals' rights over their personal information are respected.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.