AI-900 Practice Question: Describe Artificial Intelligence workloads and considerations
A company deploys an AI chatbot on its website to answer customer questions. The company wants to be transparent about the nature of the interaction. Which Microsoft responsible AI principle is most directly relevant to ensuring users know they are communicating with an AI and not a human?
⚠ Common exam trap
Microsoft often tests the distinction between transparency and accountability, where candidates mistakenly choose accountability because they confuse 'being responsible for outcomes' with 'being open about the system's nature'.
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
✓
Transparency
Transparency is the Microsoft responsible AI principle that requires AI systems to be designed so that users are aware they are interacting with an AI, not a human. In the context of a chatbot, this means clearly disclosing the AI nature of the system, such as through a label or introductory message, to avoid deception and build trust.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Inclusiveness
Why it's wrong here
Inclusiveness in Microsoft's responsible AI framework focuses on designing systems that empower everyone, avoid bias, and remain accessible to people with diverse abilities — for example, enabling screen-reader support or voice input on a website chatbot. While a chatbot should absolutely be inclusive, the scenario's key requirement is not accessibility or fairness but rather proactively telling users they are interacting with an AI. That explicit disclosure is mandated by Transparency, so Inclusiveness does not answer the question.
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Privacy and security
Why it's wrong here
Privacy and security address how an AI system protects personal data through encryption, access controls, and regulatory compliance like GDPR. A website chatbot must securely handle user information, but the scenario does not ask about data protection or system security — it asks about informing users that the entity they are chatting with is an AI. That obligation comes from Transparency, which requires clear communication about the AI's identity, not from privacy or security measures.
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Transparency
Why this is correct
Transparency is the correct responsible AI principle because it requires systems to clearly disclose when users are interacting with an AI and to provide understandable information about the AI's capabilities and limitations. In the scenario, the chatbot must explicitly tell website visitors they are speaking with an AI rather than a human, enabling users to set appropriate expectations about the interaction. This disclosure is the core of Transparency and distinguishes it from principles like accountability or privacy.
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Accountability
Why it's wrong here
Accountability ensures that humans take ownership of AI outcomes through governance, audits, and remediation processes. While a company is ultimately accountable for the behavior of its chatbot, that principle does not inherently require disclosing to users that the interaction is with an AI. The specific requirement to label or reveal the AI nature of the conversation falls under Transparency, making Accountability an incorrect choice for this question.
Go deeper
Related to this question
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Responsible AI Principles
Key term
Responsible AI
A framework of ethical principles and practices that ensure artificial intelligence systems are developed and deployed in a transparent, fair, accountable, and safe manner.
Key term
Transparency
Transparency in AI means that the inner workings, decision-making processes, and data used by an AI system are open, understandable, and auditable by humans.
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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.