Free Microsoft AB-731 Exam Dumps Questions & Answers

Which statement accurately describes the difference between a pretrained generative AI model and a fine- tuned generative AI model?

• A.A pretrained model is trained on broad datasets, while a fine-tuned model is adapted to perform well on a narrower, domain-specific dataset.
• B.A pretrained model is faster to train than a fine-tuned model because the pretrained model uses fewer parameters.
• C.A pretrained model is optimized for a specific task, while a fine-tuned model is designed for general- purpose use.
• D.A pretrained model requires labeled data, while a fine-tuned model does not.

You have a business unit that uses an AI solution to process loan applications. You discover that the solution rejects the application of all applicants that are older than 60 years of age. Which Microsoft responsible AI principle is this violating?

• A.reliability and safety
• B.transparency
• C.accountability
• D.fairness

For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation:
Answer Area
* Allowing AI models to make autonomous decisions supports the Microsoft responsible AI principle of accountability. Answer: No
* Regularly testing AI models for fairness and inclusiveness helps ensure they align with Microsoft's Responsible AI principles. Answer: Yes
* Protecting user data and limiting access to personal information supports the Microsoft responsible AI principles of privacy and security. Answer: Yes Microsoft's Responsible AI principles emphasize that people and organizations must remain accountable for AI systems and their outcomes. Accountability is strengthened by governance, human oversight, clear ownership, auditability, and processes to review and address issues-not by letting models make unchecked autonomous decisions. Therefore, statement 1 is No: increasing autonomy can actually increase risk unless paired with human-in-the-loop controls and clear escalation paths, because accountability requires clear responsibility for decisions and impacts.
Statement 2 is Yes because fairness and inclusiveness are explicitly supported through ongoing evaluation.
Regular testing helps detect disparate impact, performance gaps across user groups, and unintended bias introduced by data drift or changes in usage patterns. It's not a one-time activity; it's continuous assurance that the system behaves appropriately as conditions change.
Statement 3 is Yes because privacy and security are directly supported by protecting personal/sensitive data, enforcing least privilege access, and implementing controls such as data loss prevention, encryption, access logging, and strong identity governance. Limiting access to personal information reduces exposure and supports compliance obligations while aligning with privacy-by-design and secure-by-design expectations for AI-enabled solutions.

Your company stores thousands of reports and documents across multiple systems. You recommend using Azure AI Search as part of a new generative AI solution to improve information discovery. What is a key benefit of using Azure AI Search in this scenario?

• A.generates responses to customer questions without referencing the existing data
• B.queries and retrieves information from large collections of data by using natural language
• C.improves model accuracy by fine-tuning organizational data
• D.automates document workflows based on the document content

Your company is developing an AI-powered customer support agent. You need to ensure that the solution follows Microsoft responsible AI principles. Which two actions should you perform? Select the two BEST answers. Each correct answer presents part of the solution.

• A.Ensure that the agent can be used for multiple purposes.
• B.Provide a clear disclaimer that users are interacting with an AI solution.
• C.Test the agent to ensure that responses are inclusive and culturally sensitive.
• D.Enable the agent to operate independently.
• E.Retain all customer conversations.