Sure Pass Exam AI-900 PDF

Statement

Yes / No

Providing an explanation of the outcome of a credit loan application is an example of the Microsoft transparency principle for responsible AI.

Yes

A triage bot that prioritizes insurance claims based on injuries is an example of the Microsoft reliability and safety principle for responsible AI.

Yes

An AI solution that is offered at different prices for different sales territories is an example of the Microsoft inclusiveness principle for responsible AI.

No

This question is based on the Responsible AI principles defined by Microsoft, which are part of the AI-900 Microsoft Azure AI Fundamentals curriculum. Microsoft’s Responsible AI framework consists of six key principles: Fairness, Reliability and Safety, Privacy and Security, Inclusiveness, Transparency, and Accountability. Each principle ensures that AI systems are developed and used in a way that benefits people and society responsibly.

Transparency Principle – YesProviding an explanation for a loan decision aligns with the Transparency principle. Microsoft defines transparency as helping users and stakeholders understand how AI systems make decisions. For example, when a credit scoring AI model approves or denies a loan, explaining the factors that influenced that outcome (such as credit history or income level) ensures that customers understand the reasoning process. This builds trust and supports responsible deployment.

Reliability and Safety Principle – YesA triage bot that prioritizes insurance claims based on injury severity relates directly to Reliability and Safety. This principle ensures AI systems operate consistently, perform accurately, and produce dependable outcomes. In the case of the triage bot, it must reliably assess the input data (injury descriptions) and rank claims appropriately to avoid harm or misjudgment, aligning with Microsoft’s emphasis on designing AI systems that are safe and robust.

Inclusiveness Principle – NoAn AI solution priced differently across sales territories is not related to Inclusiveness. Inclusiveness focuses on ensuring accessibility and eliminating bias or exclusion for all users—especially those with disabilities or underrepresented groups. Pricing strategy is a business decision, not an inclusiveness issue. Therefore, this statement is No.

In summary, based on the AI-900 Responsible AI principles, the correct selections are:

The correct answer is B. Optical character recognition (OCR).

OCR is a key capability within the Computer Vision and Document Intelligence services in Azure AI that enables systems to detect and extract printed or handwritten text from images and scanned documents.

When capturing text from images, OCR technology analyzes visual patterns (shapes of letters and numbers) and converts them into machine-readable text. For example, a photo of a receipt, street sign, or printed report can be processed to extract textual content programmatically.

A (Text analysis): Applies to NLP tasks such as sentiment detection or key phrase extraction, not image processing.

C (Image description): Generates captions describing the scene or objects in an image.

D (Object detection): Identifies and locates objects but does not extract text.

According to Microsoft’s Responsible AI Principles, Transparency means that AI systems should clearly communicate how they operate, including data sources, limitations, and decision-making processes. Stating the source of data used to train a model helps users understand where the model’s knowledge comes from, enabling informed trust and accountability.

Transparency ensures that organizations disclose relevant details about data collection and model design, especially for compliance, fairness, and reproducibility.

Other options are incorrect:

A. Fairness: Focuses on avoiding bias and ensuring equitable outcomes.

C. Reliability and safety: Ensures AI performs consistently and safely.

D. Privacy and security: Protects user data and maintains confidentiality.

Thus, the principle illustrated by disclosing training data sources is Transparency.