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. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 corporation deploys an AI system that uses a deep neural network to recommend candidate profiles for job openings. The hiring managers cannot understand why a particular candidate was recommended or not. Which Microsoft responsible AI principle is most directly relevant?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Transparency
The scenario describes a deep neural network whose internal reasoning is opaque to users. Microsoft's Transparency principle requires AI systems to be interpretable and explainable, so that stakeholders can understand how decisions are made. This directly addresses the hiring managers' inability to see why a candidate was recommended or not.
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 concerns bias and discrimination, but the immediate problem is the lack of explanation for recommendations.
✗
Reliability and safety
Why it's wrong here
Reliability deals with consistent performance, not the ability to explain decisions.
✓
Transparency
Why this is correct
Transparency requires that AI systems be understandable and that decisions can be explained to stakeholders.
Related concept
Read the scenario before looking for a memorised answer.
✗
Accountability
Why it's wrong here
Accountability means responsibility for outcomes, but without transparency it is impossible to determine why a decision was made.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse Transparency (explainability) with Accountability (who is responsible) or Fairness (bias), but the core issue is the inability to understand the model's reasoning, not who to blame or whether bias exists.
Detailed technical explanation
How to think about this question
Deep neural networks are often 'black boxes' due to their non-linear transformations across many layers. Techniques like SHAP (SHapley Additive exPlanations) or LIME (Local Interpretable Model-agnostic Explanations) can approximate feature importance to provide post-hoc explanations. In practice, a hiring system lacking such interpretability tools violates the Transparency principle, as managers cannot audit or trust its recommendations.
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 healthcare organisation deploys an application with a public-facing web tier and a private database tier. The database subnet has no public IP and only accepts connections from the web tier's security group. Questions like this test whether you can design cloud network isolation using VNets/VPCs, subnets, and security group rules.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this AI-900 question in full detail.
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: Transparency — The scenario describes a deep neural network whose internal reasoning is opaque to users. Microsoft's Transparency principle requires AI systems to be interpretable and explainable, so that stakeholders can understand how decisions are made. This directly addresses the hiring managers' inability to see why a candidate was recommended or not.
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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Question Discussion
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