AI-900 Practice Question: Describe Artificial Intelligence workloads and considerations
A healthcare start-up proposes a fully automated AI system to diagnose patients from medical scans without any human doctor review. They claim the system is 99% accurate. According to Microsoft's responsible AI principles, which principle is most directly violated by removing human oversight from this critical decision-making process?
⚠ Common exam trap
Candidates often confuse accountability with transparency or reliability, assuming that a highly accurate system is inherently trustworthy, but Microsoft's principles explicitly require human responsibility for outcomes, not just system performance.
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
✓
Accountability
Removing human oversight from a fully automated diagnostic system violates the accountability principle. Microsoft's responsible AI principle of accountability requires that humans remain responsible for AI-driven decisions, especially in high-stakes healthcare scenarios where errors can have life-or-death consequences. By eliminating any human doctor review, the start-up fails to ensure that a human can intervene, validate, or take responsibility for the system's outputs.
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 concerns the equitable treatment of patients across different demographic groups, ensuring the system does not introduce or amplify biases in diagnosis or treatment recommendations. While fairness is a critical requirement for any clinical AI, it is not the core issue indicated by the scenario, which centers on the absence of a human in the loop to take responsibility. A fully automated system could be fair and still violate accountability, because no human can be held accountable for its mistakes.
When this WOULD be correct
A question that asks: 'An AI system for loan approvals consistently denies loans to a specific ethnic group. Which principle is violated?' In that case, fairness is the correct answer because the system exhibits discriminatory bias.
- ✗
Reliability and safety
Why it's wrong here
Reliability and safety focus on whether the system performs correctly and consistently under normal and adversarial conditions, such as avoiding misdiagnoses or maintaining safe operation. A fully automated system could in principle be designed to be highly reliable and safe, passing rigorous validation and monitoring, so the central problem is not necessarily a failure of reliability. The key deficiency is the lack of human oversight, which is directly addressed by the accountability principle.
When this WOULD be correct
A question asks: 'An AI system for autonomous driving has a 99.9% accuracy but fails in rare edge cases causing accidents. Which principle is most violated?' Here, reliability and safety would be correct because the system's failures pose direct safety risks.
- ✗
Transparency
Why it's wrong here
Transparency in AI refers to the degree to which the system's decisions and inner workings can be understood and audited by humans. In this scenario, a fully automated diagnosis system might still be transparent (e.g., with explainable inputs and confidence scores), so the absence of human involvement is not fundamentally a transparency violation. The principle that most directly addresses the lack of human oversight is accountability, because it requires a designated party to answer for outcomes and take corrective action.
When this WOULD be correct
A question asks: 'An AI system provides loan approval decisions without explaining the reasons. Which principle is violated?' In that scenario, transparency is correct because the system fails to provide understandable explanations for its decisions.
- ✓
Accountability
Why this is correct
Accountability is a foundational principle of responsible AI, requiring that human beings remain responsible for the design, deployment, and outcomes of AI systems, especially in high-stakes domains like healthcare. Fully automating diagnosis removes the possibility of a human clinician to verify, override, or accept the AI's recommendation, thereby eliminating a clear line of responsibility for patient outcomes. Even if the system is technically reliable, accountability demands that there is a human who can be held responsible for the system's decisions and its consequences. This is the core issue in the scenario.
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The AI-900 exam frequently reuses these exact scenarios with slightly different constraints.
✓AccountabilityCorrect answer▾
Why this is correct
Accountability is a foundational principle of responsible AI, requiring that human beings remain responsible for the design, deployment, and outcomes of AI systems, especially in high-stakes domains like healthcare. Fully automating diagnosis removes the possibility of a human clinician to verify, override, or accept the AI's recommendation, thereby eliminating a clear line of responsibility for patient outcomes. Even if the system is technically reliable, accountability demands that there is a human who can be held responsible for the system's decisions and its consequences. This is the core issue in the scenario.
✗FairnessWrong answer — click to see why▾
Why this is wrong here
The question focuses on removing human oversight, which directly violates accountability (the need for human responsibility), not fairness. Fairness is about bias and equitable treatment, not about oversight.
★ When this WOULD be the correct answer
A question that asks: 'An AI system for loan approvals consistently denies loans to a specific ethnic group. Which principle is violated?' In that case, fairness is the correct answer because the system exhibits discriminatory bias.
Why candidates choose this
Candidates may think that removing human review leads to unfair outcomes, confusing the lack of oversight with potential bias, but the core violation here is accountability, not fairness.
✗Reliability and safetyWrong answer — click to see why▾
Why this is wrong here
The question emphasizes removal of human oversight, which directly violates accountability (who is responsible for outcomes). Reliability and safety concerns (e.g., accuracy) are secondary; the core issue is lack of human accountability.
★ When this WOULD be the correct answer
A question asks: 'An AI system for autonomous driving has a 99.9% accuracy but fails in rare edge cases causing accidents. Which principle is most violated?' Here, reliability and safety would be correct because the system's failures pose direct safety risks.
Why candidates choose this
Candidates may think '99% accurate' implies reliability issues, and removing human oversight seems unsafe, so they mistakenly prioritize reliability and safety over the accountability principle.
✗TransparencyWrong answer — click to see why▾
Why this is wrong here
Transparency is about providing clear information about AI system capabilities and limitations, but the core issue here is removing human oversight, which directly violates the accountability principle that requires human responsibility for AI decisions.
★ When this WOULD be the correct answer
A question asks: 'An AI system provides loan approval decisions without explaining the reasons. Which principle is violated?' In that scenario, transparency is correct because the system fails to provide understandable explanations for its decisions.
Why candidates choose this
Candidates may confuse transparency with accountability, thinking that if the system is not transparent about its decision-making, it also lacks accountability. However, the specific violation here is the absence of human oversight, not lack of explanation.
Analysis generated from the official AI-900blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
Go deeper
Related to this question
Learn chapter
Responsible AI Principles
Key term
Accountability
Accountability is the security principle that ensures actions and identity are linked so that a person or system can be held responsible for their activities.
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.
About these practice questions
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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.