- A
Fairness
Why wrong: Fairness addresses biases in AI that could lead to discrimination, but the primary concern here is physical safety, not differential treatment of individuals.
- B
Privacy and security
Why wrong: Privacy and security focus on protecting data and preventing unauthorized access. While important, the core issue is the robot's inability to detect pedestrians safely, not data handling.
- C
Reliability and safety
Reliability and safety ensure AI systems perform as intended and do not cause harm. The robot's detection failures in low light present a safety risk that must be mitigated.
- D
Transparency
Why wrong: Transparency means explaining AI decisions, but the immediate need is to make the system safe, not to explain its failures to pedestrians.
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.
An autonomous delivery robot uses AI to navigate sidewalks. The robot occasionally fails to detect pedestrians in low-light conditions, leading to near-collisions. The company wants to ensure the system is robust and safe before wider deployment. Which Microsoft responsible AI principle is most directly relevant?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Reliability and safety
The robot's failure to detect pedestrians in low-light conditions directly impacts the system's ability to operate reliably and safely. The Reliability and safety principle in Microsoft's responsible AI framework requires that AI systems perform consistently under expected conditions and fail gracefully when they cannot. Ensuring the robot can handle edge cases like low light is a core safety requirement before deployment.
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 addresses biases in AI that could lead to discrimination, but the primary concern here is physical safety, not differential treatment of individuals.
- ✗
Privacy and security
Why it's wrong here
Privacy and security focus on protecting data and preventing unauthorized access. While important, the core issue is the robot's inability to detect pedestrians safely, not data handling.
- ✓
Reliability and safety
Why this is correct
Reliability and safety ensure AI systems perform as intended and do not cause harm. The robot's detection failures in low light present a safety risk that must be mitigated.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Transparency
Why it's wrong here
Transparency means explaining AI decisions, but the immediate need is to make the system safe, not to explain its failures to pedestrians.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse Transparency (which involves disclosing limitations) with the actual requirement to engineer the system to be safe and reliable, but the question asks for the principle most directly relevant to preventing near-collisions, which is Reliability and safety.
Detailed technical explanation
How to think about this question
Under the hood, reliability and safety in autonomous systems often involve redundant sensor fusion (e.g., combining LiDAR, radar, and cameras) and fallback behaviors when primary sensors degrade. For example, a robot might switch to ultrasonic sensors or reduce speed in low-light conditions to maintain safe operation. Real-world deployments like autonomous delivery robots from Nuro or Starship explicitly test for such edge cases to meet safety standards.
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.
What to study next
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FAQ
Questions learners often ask
What does this AI-900 question test?
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: Reliability and safety — The robot's failure to detect pedestrians in low-light conditions directly impacts the system's ability to operate reliably and safely. The Reliability and safety principle in Microsoft's responsible AI framework requires that AI systems perform consistently under expected conditions and fail gracefully when they cannot. Ensuring the robot can handle edge cases like low light is a core safety requirement before deployment.
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.
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Last reviewed: Jun 11, 2026
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.
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