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An e-commerce company deploys an AI-powered robot for warehouse inventory management. The robot uses computer vision to navigate and pick items. In certain lighting conditions, the robot misidentifies empty shelves and attempts to pick items that are not there, causing damage. According to Microsoft's Responsible AI principles, which principle is most directly concerned with ensuring the robot performs correctly and safely under expected conditions?

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An e-commerce company deploys an AI-powered robot for warehouse inventory management. The robot uses computer vision to navigate and pick items. In certain lighting conditions, the robot misidentifies empty shelves and attempts to pick items that are not there, causing damage. According to Microsoft's Responsible AI principles, which principle is most directly concerned with ensuring the robot performs correctly and safely under expected conditions?

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

Fairness

Fairness addresses potential biases in AI systems that could lead to unfair treatment of groups, not the operational reliability or safety of the system.

B

Best answer

Reliability and Safety

This principle requires AI systems to perform reliably and safely under normal and adverse conditions, which directly applies to the robot's malfunctions due to lighting.

C

Distractor review

Privacy and Security

Privacy and Security focus on protecting data from unauthorized access and ensuring secure system operation, not on physical safety or operational correctness.

D

Distractor review

Transparency

Transparency is about making AI systems understandable and providing explanations for their decisions, not about preventing physical failures.

Common exam trap

Common exam trap: answer the scenario, not the keyword

Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.

Technical deep dive

How to think about this question

This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.

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.
  • Use explanations to understand the rule behind the answer.

TExam Day Tips

  • Underline the problem statement mentally.
  • 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.

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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Question 5

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Question 6

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FAQ

Questions learners often ask

What does this AI-900 question test?

Read the scenario before looking for a memorised answer.

What is the correct answer to this question?

The correct answer is: Reliability and Safety — The Responsible AI principle of Reliability and Safety focuses on ensuring that AI systems operate as intended, are robust to a variety of conditions, and do not cause harm. In this scenario, the robot's failure under specific lighting conditions directly challenges its reliability and safety. The other principles address different concerns: Fairness is about bias and equity, Privacy and Security is about data protection, and Transparency is about explainability. Thus, Reliability and Safety is the most relevant principle.

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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