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Microsoft AI-900 Exam (page: 2)
Microsoft Azure AI Fundamentals
Updated on: 25-Aug-2025

Viewing Page 2 of 36
AI-900 PDF 273 Questions

What are three Microsoft guiding principles for responsible AI? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

  1. knowledgeability
  2. decisiveness
  3. inclusiveness
  4. fairness
  5. opinionatedness
  6. reliability and safety

Answer(s): C,D,F


Reference:

https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles



When you design an AI system to assess whether loans should be approved, the factors used to make the decision should be explainable.
This is an example of which Microsoft guiding principle for responsible AI?

  1. transparency
  2. inclusiveness
  3. fairness
  4. privacy and security

Answer(s): A

Explanation:

Achieving transparency helps the team to understand the data and algorithms used to train the model, what transformation logic was applied to the data, the final model generated, and its associated assets. This information offers insights about how the model was created, which allows it to be reproduced in a transparent way.
Incorrect Answers:
B: Inclusiveness mandates that AI should consider all human races and experiences, and inclusive design practices can help developers to understand and address potential barriers that could unintentionally exclude people. Where possible, speech-to-text, text-to-speech, and visual recognition technology should be used to empower people with hearing, visual, and other impairments.
C: Fairness is a core ethical principle that all humans aim to understand and apply. This principle is even more important when AI systems are being developed. Key checks and balances need to make sure that the system's decisions don't discriminate or run a gender, race, sexual orientation, or religion bias toward a group or individual.
D: A data holder is obligated to protect the data in an AI system, and privacy and security are an integral part of this system. Personal needs to be secured, and it should be accessed in a way that doesn't compromise an individual's privacy.


Reference:

https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/strategy/responsible-ai



HOTSPOT (Drag and Drop is not supported)
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:




Box 1: Yes
Achieving transparency helps the team to understand the data and algorithms used to train the model, what transformation logic was applied to the data, the final model generated, and its associated assets. This information offers insights about how the model was created, which allows it to be reproduced in a transparent way.
Box 2: No
A data holder is obligated to protect the data in an AI system, and privacy and security are an integral part of this system. Personal needs to be secured, and it should be accessed in a way that doesn't compromise an individual's privacy.
Box 3: No
Inclusiveness mandates that AI should consider all human races and experiences, and inclusive design practices can help developers to understand and address potential barriers that could unintentionally exclude people. Where possible, speech-to-text, text-to-speech, and visual recognition technology should be used to empower people with hearing, visual, and other impairments.


Reference:

https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai



DRAG DROP (Drag and Drop is not supported)
Match the principles of responsible AI to the appropriate requirements.
To answer, drag the appropriate principles from the column on the left to its requirement on the right. Each principle may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Select and Place:

  1. See Explanation section for answer.

Answer(s): A

Explanation:


Reference:

https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles



You are building an AI-based app.
You need to ensure that the app uses the principles for responsible AI.
Which two practices should you follow? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

  1. Implement an Agile software development methodology
  2. Implement a process of AI model validation as part of the software review process
  3. Establish a risk governance committee that includes members of the legal team, members of the risk management team, and a privacy officer
  4. Prevent the disclosure of the use of AI-based algorithms for automated decision making

Answer(s): B,C


Reference:

https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/3-implications-responsible-ai-practical



HOTSPOT (Drag and Drop is not supported)
Select the answer that correctly completes the sentence.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:




Fairness is a core ethical principle that all humans aim to understand and apply. This principle is even more important when AI systems are being developed. Key checks and balances need to make sure that the system's decisions don't discriminate or run a gender, race, sexual orientation, or religion bias toward a group or individual.


Reference:

https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai



DRAG DROP (Drag and Drop is not supported)
Match the principles of responsible AI to the appropriate descriptions.
To answer, drag the appropriate principle from the column on the left to its description on the right. Each principle may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Select and Place:

  1. See Explanation section for answer.

Answer(s): A

Explanation:




Box 1: Reliability and safety
Reliability and safety: AI systems should perform reliably and safely.
Box 2: Privacy and security
Privacy and security: AI systems should be secure and respect privacy.
Incorrect:
Inclusiveness: AI systems should empower everyone and engage people. Fairness: AI systems should treat all people fairly.


Reference:

https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/strategy/responsible-ai



During the process of Machine Learning, when should you review evaluation metrics?

  1. Before you train a model.
  2. After you clean the data.
  3. Before you choose the type of model.
  4. After you test a model on the validation data.

Answer(s): D



Viewing Page 2 of 36



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OLERATO 7/1/2025 5:44:14 AM

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