Microsoft Azure AI Fundamentals (AI-900)Describe AI workloads and considerationsMedium
A financial institution is deploying an AI system to automate loan approvals. The system's decisions must be fully auditable, and regulators require a clear explanation for every loan denial, detailing the specific factors that led to the rejection. Which responsible AI principle is paramount in this requirement?
- AReliability and Safety
- BInclusiveness
- CPrivacy and Security
- DTransparency
Show answer & explanationAnswer & explanation
Correct answer: D. Transparency
Transparency ensures that AI systems are understandable and their decisions can be explained. The requirement for 'clear explanation for every loan denial, detailing the specific factors' directly aligns with this principle, often referred to as explainable AI (XAI).
Why the other options are wrong
- A. Reliability and Safety ensure consistent and safe operation, but don't specifically mandate explaining decision logic.
- B. Inclusiveness ensures accessibility and broad empowerment, not the detailed explanation of a decision.
- C. Privacy and Security focus on data protection, not the explainability of decisions.
Responsible AI: Transparency
The principle that AI systems should be understandable, and their decision-making processes should be explainable.
- Enables users to comprehend how an AI system works.
- Crucial for debugging, auditing, and building trust.
- Often involves Explainable AI (XAI) techniques.
Memory trick: AI decisions need to be TRANSPARENT, like a glass box.