The correct answers are derived from the Microsoft Azure AI Fundamentals (AI-900) Official Study Guide and the Microsoft Learn module “Identify guiding principles for responsible AI.”

Microsoft defines six core principles of Responsible AI:

Fairness

Reliability and safety

Privacy and security

Inclusiveness

Transparency

Accountability

Each principle addresses a key ethical and operational requirement for developing and deploying trustworthy AI systems.

Reliability and safety – “AI systems must consistently operate as intended, even under unexpected conditions.”This principle ensures that AI models are dependable, robust, and perform accurately under diverse circumstances. Microsoft emphasizes that systems should be thoroughly tested and monitored to guarantee predictable behavior, prevent harm, and maintain safety. A reliable AI solution should continue to function properly when faced with unusual or noisy inputs, and fail safely when issues arise. This principle focuses on stability, testing, and dependable performance.

Privacy and security – “AI systems must protect and secure personal and business information.”This principle ensures that AI systems comply with data privacy laws and ethical standards. It protects users’ sensitive data against unauthorized access and misuse. Microsoft highlights that organizations must implement strong encryption, data anonymization, and access control mechanisms to maintain confidentiality. Protecting user data is essential to building trust and compliance with global standards like GDPR.

Other principles such as fairness and inclusiveness apply to ensuring equitable and accessible AI, but they do not directly relate to system operation or information protection.

✅ Final Answers:

“Operate as intended” → Reliability and safety

“Protect and secure information” → Privacy and security