The answer is transparency, because the scenario describes an AI system that cannot explain its decision to deny a credit limit increase, which directly violates Microsoft’s responsible AI principle requiring that systems be understandable and their decisions explainable to users. This principle demands that when an AI system has a significant impact on individuals, such as denying credit, the organization must be able to provide a clear rationale for the outcome—something a complex deep neural network, by its opaque nature, cannot do. On the AI-900 exam, this question tests your ability to match a real-world scenario to the correct principle, often using a trap where you might confuse transparency with accountability or fairness; remember that transparency is specifically about explainability and openness of decision-making. A quick memory tip: if the AI is a “black box” that can’t talk, think “transparency = see-through explanation.”
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 financial institution uses an AI system to recommend credit limits for new customers. When a customer is declined for a credit limit increase, the customer asks why, but the institution cannot provide any explanation because the model is a complex deep neural network and the decision-making process is opaque. Which Microsoft responsible AI principle is most directly violated?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Transparency
The correct answer is A, Transparency. The scenario describes a deep neural network that cannot explain its decision to deny a credit limit increase, which directly violates the transparency principle. Microsoft's responsible AI principle of transparency requires that AI systems be understandable and that their decisions can be explained to users, especially when those decisions have significant impact on individuals.
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.
✓
Transparency
Why this is correct
Correct. Transparency requires that AI systems are understandable and decisions can be explained. Without an explanation, the principle is violated.
Related concept
Read the scenario before looking for a memorised answer.
✗
Reliability and safety
Why it's wrong here
Reliability and safety focus on the system performing correctly and without causing harm, not on explainability.
✗
Fairness
Why it's wrong here
Fairness addresses bias and ensuring equitable treatment, not the ability to explain decisions.
✗
Privacy and security
Why it's wrong here
Privacy and security concern data protection and secure access, not the explainability of decisions.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse the inability to explain a decision with a fairness or reliability issue, but the core violation is the lack of transparency, not bias or system failure.
Detailed technical explanation
How to think about this question
Deep neural networks are often considered 'black boxes' due to their hierarchical, non-linear transformations across many layers, making it difficult to trace which input features drove a specific output. Techniques like SHAP (SHapley Additive exPlanations) or LIME (Local Interpretable Model-agnostic Explanations) can provide post-hoc explanations, but the model itself lacks inherent interpretability. In regulated industries like finance, the inability to provide explanations can violate regulations such as the GDPR's right to explanation, making transparency a critical requirement.
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 correct answer is A, Transparency. The scenario describes a deep neural network that cannot explain its decision to deny a credit limit increase, which directly violates the transparency principle. Microsoft's responsible AI principle of transparency requires that AI systems be understandable and that their decisions can be explained to users, especially when those decisions have significant impact on individuals.
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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A university deploys an AI model to predict which students are at risk of dropping out. The predictions are used to offer targeted support. Students who may be negatively impacted by this prediction have the right to understand how the model arrived at its decision. Which Microsoft responsible AI principle is most directly relevant?
hard
A.Fairness
B.Reliability and safety
✓ C.Transparency
D.Privacy and security
Why C: Transparency is the responsible AI principle that requires AI systems to be understandable and interpretable. In this scenario, students have the right to know how the model arrived at its dropout prediction, which directly aligns with transparency's goal of providing clear explanations for AI decisions. This principle ensures that affected individuals can access meaningful information about the logic and factors used by the model.
Variation 2. Which AI principle ensures that AI systems are developed and used in ways that are transparent and understandable to affected stakeholders?
easy
A.Reliability
B.Fairness
✓ C.Transparency
D.Privacy
Why C: Transparency is the correct answer because it directly addresses the requirement that AI systems be open, explainable, and understandable to stakeholders. This principle ensures that decisions made by AI models can be audited, interpreted, and communicated clearly, which is essential for building trust and enabling informed consent.
Variation 3. A healthcare research organization publishes an AI system that diagnoses skin conditions from images. In a study, they discover that the model's accuracy is significantly lower for people with darker skin tones compared to those with lighter skin tones. According to Microsoft's Responsible AI principles, which principle most directly requires the organization to disclose this limitation in their documentation?
medium
A.Fairness
✓ B.Transparency
C.Accountability
D.Privacy and Security
Why B: The Transparency principle requires AI systems to be understandable and for their limitations to be clearly communicated. In this scenario, the organization must disclose the model's lower accuracy for darker skin tones because users and clinicians need to know when the system is less reliable to make informed decisions. Without this disclosure, the system could be misused or trusted inappropriately, violating the core tenet of transparency.
Last reviewed: Jun 11, 2026
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