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. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 bank uses an AI system to approve loan applications. The bank wants to ensure that applicants can understand why a loan was approved or rejected. Which Microsoft responsible AI principle is most directly relevant to this requirement?
Why wrong: Fairness is about ensuring AI systems do not discriminate, not about explaining individual decisions.
B
Inclusiveness
Why wrong: Inclusiveness focuses on designing systems that work for all people, not on transparency.
C
Transparency
Transparency requires that AI decisions be interpretable and explainable, which directly addresses the need for applicants to understand loan decisions.
D
Reliability and Safety
Why wrong: Reliability and Safety ensure the system operates correctly and safely, but do not inherently provide explanations.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Transparency
The requirement that applicants can understand why a loan was approved or rejected directly aligns with the Transparency principle, which mandates that AI systems be interpretable and that decisions be explainable to users. In this context, the bank must provide clear reasoning for loan outcomes, enabling applicants to comprehend the factors influencing the decision, such as credit score thresholds or income verification rules.
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 is about ensuring AI systems do not discriminate, not about explaining individual decisions.
✗
Inclusiveness
Why it's wrong here
Inclusiveness focuses on designing systems that work for all people, not on transparency.
✓
Transparency
Why this is correct
Transparency requires that AI decisions be interpretable and explainable, which directly addresses the need for applicants to understand loan decisions.
Related concept
Read the scenario before looking for a memorised answer.
✗
Reliability and Safety
Why it's wrong here
Reliability and Safety ensure the system operates correctly and safely, but do not inherently provide explanations.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse Transparency with Fairness, mistakenly thinking that explaining a decision inherently ensures it is fair, whereas Transparency is solely about providing understandable reasoning, not about the decision's ethical correctness.
Detailed technical explanation
How to think about this question
In practice, Transparency is often implemented through techniques like feature importance scores (e.g., SHAP or LIME) or rule-based explanations that map input features to outputs. For example, a loan approval model might output a reason code indicating 'low credit score' or 'high debt-to-income ratio,' which the bank can present to the applicant. This principle also intersects with regulatory requirements like the GDPR's right to explanation, which mandates that automated decisions be explainable to affected individuals.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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 requirement that applicants can understand why a loan was approved or rejected directly aligns with the Transparency principle, which mandates that AI systems be interpretable and that decisions be explainable to users. In this context, the bank must provide clear reasoning for loan outcomes, enabling applicants to comprehend the factors influencing the decision, such as credit score thresholds or income verification rules.
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 →
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.