This question tests understanding of Microsoft’s six guiding principles for Responsible AI, which are: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. These principles, as described in the Microsoft Azure AI Fundamentals (AI-900) study guide and Microsoft Learn Responsible AI module, help ensure that AI systems are developed and used ethically and responsibly.

Transparency – Yes:Transparency means users should understand how and why an AI system makes certain decisions. Providing an explanation of the outcome of a credit loan application clearly supports transparency because it helps customers know the reasoning behind approval or rejection. According to Microsoft Learn, transparency ensures that “AI systems are understandable by users and stakeholders,” especially in sensitive applications such as finance and credit scoring. Thus, the first statement is Yes.

Reliability and Safety – Yes:The reliability and safety principle ensures AI systems perform consistently, safely, and as intended, even in complex or high-risk environments. A triage bot that prioritizes insurance claims based on injury type aligns with this principle—it must be accurate, dependable, and safe to ensure claims are processed correctly and not influenced by errors or faulty algorithms. Microsoft teaches that AI should be “reliable under expected and unexpected conditions” to prevent harm or misjudgment. Therefore, this statement is Yes.

Inclusiveness – No:Inclusiveness focuses on ensuring AI systems empower and benefit all users, especially those with different abilities or backgrounds. Offering an AI solution at different prices across sales territories is a business decision, not an ethical or inclusiveness principle issue. It does not relate to accessibility or equal participation of diverse users. Therefore, this final statement is No.