A bank is developing an AI system to automatically approve or reject small personal loans. To ensure the system treats applicants fairly regardless of race, gender, or age, which Microsoft responsible AI principle is most directly relevant?
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.
Distractor review
Inclusiveness
Inclusiveness is about making AI accessible to people of all abilities and backgrounds, not specifically about preventing discrimination in outcomes.
Best answer
Fairness
Fairness directly addresses avoiding bias and ensuring equitable treatment across demographic groups, which is critical for loan approval decisions.
Distractor review
Reliability and safety
Reliability and safety concern the accuracy and robustness of the AI system under various conditions, not fairness across populations.
Distractor review
Transparency
Transparency relates to making the AI's behavior and decisions understandable, which supports fairness but is not the primary principle for non-discrimination.
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 in AI emphasizes that systems should treat all people fairly and avoid discrimination. In this loan approval scenario, the bank must ensure the model does not produce biased outcomes based on protected attributes. Inclusiveness (A) focuses on designing for accessibility and diverse user needs. Reliability and safety (C) focuses on accuracy and robustness under normal and adverse conditions. Transparency (D) is about ensuring decisions are understandable and explainable to stakeholders.
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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