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AI-900 Practice Question: Describe Artificial Intelligence workloads and considerations

Which responsible AI principle focuses on protecting personal information and ensuring AI systems handle data with appropriate privacy safeguards?

⚠ Common exam trap

Watch out — candidates often confuse 'privacy and security' with 'accountability' because both involve governance, but privacy specifically concerns data protection mechanisms, not just who is responsible for the system.

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

Privacy and security

Privacy and security is the correct responsible AI principle because it directly addresses the protection of personal data and the implementation of safeguards such as encryption, access controls, and data minimization. In AI systems, this principle ensures that sensitive information (e.g., PII) is handled in compliance with regulations like GDPR and that models do not inadvertently leak training data through inference attacks.

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 is a responsible AI principle focused on mitigating bias and ensuring that AI models produce equitable outcomes across demographic groups such as race, gender, or age. It does not govern the handling, consent, or protection of individuals' personal information, which is precisely the domain of privacy and security. Therefore, while fairness is essential for ethical AI, it does not match the specific requirement of safeguarding personal data.

  • Privacy and security

    Why this is correct

    Privacy and security is the correct responsible AI principle because it directly addresses the protection of personal data, honoring individual privacy rights, and implementing controls to prevent unauthorized access, misuse, or leaks. In this scenario, the AI system handling personal information must enforce data minimization, encryption, access controls, and compliance with regulations like GDPR. This principle ensures that users' sensitive details remain confidential and that the system itself is resilient to attacks, which is exactly what the question describes.

  • Inclusiveness

    Why it's wrong here

    Inclusiveness aims to ensure that AI systems are designed to benefit all people, including those with disabilities or from underrepresented backgrounds, by removing barriers and promoting universal access. It does not specifically cover the technical or procedural safeguards needed to protect personal information from unauthorized use or disclosure. While both are core pillars of responsible AI, inclusiveness addresses who the AI serves, not how sensitive data is secured.

  • Accountability

    Why it's wrong here

    Accountability establishes that humans are responsible for the outcomes of AI systems, typically through governance structures, role definitions, and audit trails that track decisions and actions. It is about ensuring transparency and answerability for AI behavior, not about protecting the privacy or confidentiality of personal data handled by the system. The question's focus on safeguarding personal information aligns with privacy and security, not with the governance-oriented principle of accountability.

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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.