Chapter 1 of 7 · Microsoft AI-901

Principles of Responsible AI

Microsoft's six principles, from fairness and safety to privacy, inclusiveness, transparency and accountability.

  • 2topics
  • 10 minfast track
  • 1diagrams and exhibits

Topics in this chapter

Take them in order, or jump to the one you need.

  1. 1Fairness, Reliability and SafetyAI-901 responsible AI: fairness measured per group, counterfactual testing, reliability and safety, content filters, red teaming…Diagram5 min
  2. 2Privacy, Security, Inclusiveness, Transparency and AccountabilityAI-901 responsible AI: privacy and security, inclusiveness, transparency and accountability, with consent, managed identities and…5 min

About this chapter

What this chapter covers

Microsoft builds its AI guidance on six principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency and accountability. This chapter explains what each one asks of a team that builds an AI solution, and the practical measures that put it into effect.

The questions describe a situation, such as a loan model treating two groups differently, and ask which principle is involved or which action helps.

How the topics fit together

The six principles fall into two groups of pages.

Fairness and safetytreat people equally, behave reliablyPrivacy, inclusion and trustprotect data, include everyone, explain and own the system
  • Fairness, reliability and safety covers measuring bias, testing, content filtering and the layers that reduce harm.
  • Privacy, security, inclusiveness, transparency and accountability covers protecting data, designing for everyone, explaining how the system works and keeping people answerable.
Exam tip

Learn one example action for each principle. A question that names the action, for example "require human review of high impact decisions", is usually asking you to name the principle it supports.

How to use these pages

Each topic page has the same shape, so you can skim for what you need.

  • What it is: the idea in plain words.
  • How it works: the mechanism, with examples and tables.
  • What to remember for the exam: the facts to memorise and how questions are phrased.
  • Common mistakes: the classic traps.
  • Check yourself: three questions to test your understanding.

Ready for more practice?

The full Microsoft AI-901 question bank has 511 questions, with timed practice exams and an explanation for every answer.

This study guide is independent and is not affiliated with, endorsed by, or sponsored by Microsoft. Vendor names, certification names and exam codes are trademarks of their respective owners and are used for identification only.