Question 1hardmultiple choice
Full question →hardmultiple choiceObjective-mapped
A hospital deploys an AI system to recommend treatment plans for patients. After deployment, the system is found to have significantly lower accuracy for patients from certain racial and ethnic groups because historical medical data for those groups is sparse. Which Microsoft responsible AI principle should the hospital prioritize to address this issue?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Distractor review
Inclusiveness
Inclusiveness aims to empower everyone and ensure AI benefits all people, but the core problem is unequal performance, which is a fairness concern. Inclusiveness is broader and does not specifically focus on eliminating outcome disparities.
B
Best answer
Fairness
Fairness directly addresses biases that cause an AI system to perform poorly for certain demographic groups. Prioritizing fairness involves seeking more representative data or adjusting the model to reduce disparities.
C
Distractor review
Transparency
Transparency is about being open about how the AI system works and its limitations. While important, it does not directly fix the accuracy disparity; it would only explain why it happens.
D
Distractor review
Accountability
Accountability ensures that people are responsible for AI systems and their outcomes. It does not directly address the performance gap; it focuses on governance and oversight.
Common exam trap
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Technical deep dive
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
Related practice questions
Related AI-900 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
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FAQ
Questions learners often ask
What does this AI-900 question test?
Static NAT maps one inside address to one outside address.
What is the correct answer to this question?
The correct answer is: Fairness — The fairness principle requires AI systems to treat all people equitably and avoid biases that disadvantage specific groups. The lower accuracy for certain racial/ethnic groups is a fairness issue because the system does not perform equally well for all. Inclusiveness is about empowering everyone, but fairness directly addresses the bias in outcomes. Transparency and accountability are important but secondary here; the root cause is bias due to data sparsity.
What should I do if I get this AI-900 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
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