AI-900 Practice Question: Describe Artificial Intelligence workloads and considerations
A healthcare company develops an AI system to recommend treatment plans. The system sometimes provides recommendations that contradict standard medical guidelines, leading to potential patient harm. Which Microsoft responsible AI principle is most directly violated?
⚠ Common exam trap
Many exam-takers confuse 'safety' with 'fairness' or 'privacy,' but the key indicator is the direct mention of 'patient harm' and 'contradicting standard medical guidelines,' which points squarely to the Reliability and safety principle.
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
✓
Reliability and safety
The system's recommendations contradicting standard medical guidelines and causing potential patient harm directly violates the Reliability and safety principle. This principle requires AI systems to perform consistently, safely, and as intended, especially in high-stakes domains like healthcare where failures can lead to injury or death. The scenario describes a lack of robustness and failure to meet expected safety standards, which is the core concern of this principle.
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 preventing models from discriminating on the basis of protected attributes such as race, gender, or age. In this scenario, the AI's harmful recommendations are not described as disparately impacting any specific demographic group; the failure affects all patients uniformly. The root problem is that the model produces clinically incorrect outputs, which points to a reliability deficiency rather than a bias or equity issue.
- ✓
Reliability and safety
Why this is correct
The reliability and safety principle demands that AI systems operate accurately, consistently, and without posing unreasonable physical or psychological harm to users—especially in high-stakes domains like healthcare. A system that gives harmful, incorrect medical recommendations directly violates this principle because it can lead to patient injury or death. Even if the model's outputs are unbiased and fair across groups, unreliable suggestions are unsafe and unacceptable for clinical use.
- ✗
Privacy and security
Why it's wrong here
Privacy and security specifically address how AI systems protect the confidentiality, integrity, and availability of sensitive data, including patient records and personally identifiable information. The scenario describes an output-quality problem—wrong recommendations—not a data breach, unauthorized access, or improper data handling. Since patient data is not compromised, this principle is not the primary one being violated.
- ✗
Inclusiveness
Why it's wrong here
Inclusiveness focuses on making AI systems accessible and useful for people of all abilities and backgrounds, including those with disabilities, different languages, or limited technical proficiency. The described failure is that the system gives harmful advice to any patient who receives it, not that certain patient groups are excluded from using the system. While broadening the training data to include more diverse populations could sometimes improve reliability, inclusiveness as a principle is orthogonal to the immediate safety issue.
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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
Reliability and safety
Reliability and safety in IT means that systems consistently perform their intended functions without failure and that they operate without causing harm to people, data, or the environment.
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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.