Microsoft Azure AI Fundamentals (AI-901 Korean Version) - AI-901 Korean Free Exam Questions

QUESTION NO: 1
문장을 올바르게 완성하는 답을 고르시오.
Correct Answer:

Explanation:

Evaluating model outcomes across demographic groups to reduce bias is an example of the Microsoft responsible AI principle of fairness .
The Microsoft responsible AI principle of fairness means AI systems should treat all people fairly and avoid unfair bias or discrimination across groups.
The other options are incorrect:
accountability means people and organizations remain responsible for AI systems and their effects.
privacy and security focuses on protecting data and controlling access.
transparency means users should understand when and how AI is being used, including system capabilities and limitations.
QUESTION NO: 2
당신은 인공지능 기반 고객 지원 애플리케이션을 개발하고 있습니다.
다음 작업 중 마이크로소프트의 책임 있는 AI 원칙인 포용성을 보여주는 예는 무엇입니까?

Correct Answer: A Vote an answer
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QUESTION NO: 3
문장을 올바르게 완성하는 답을 고르시오.
Correct Answer:

Explanation:

The completed sentence is:
Ensuring that human reviewers oversee AI-generated decisions and remain responsible for the final output is an example of the Microsoft responsible AI principle of accountability .
Accountability means people and organizations remain responsible for AI systems and their effects. Human review and responsibility for final decisions are examples of accountability.
The other options are incorrect:
fairness focuses on avoiding bias and treating people fairly.
privacy and security focuses on protecting data and restricting access.
transparency focuses on explaining AI use, capabilities, and limitations.
QUESTION NO: 4
채용 결정을 지원하기 위해 AI 시스템을 도입합니다.
회사 정책에 따라 사람이 AI가 생성한 추천 사항을 검토하고 최종 채용 결정에 대한 책임을 져야 합니다.
이것은 마이크로소프트의 어떤 AI 원칙의 예시인가요?

Correct Answer: D Vote an answer
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QUESTION NO: 5
책임 있는 AI의 원칙을 적절한 설명과 연결하세요.
답을 선택하려면 왼쪽 열에서 적절한 원리를 드래그하여 조명 설명에 놓으세요. 각 원리는 한 번, 여러 번 또는 전혀 사용되지 않을 수 있습니다.
참고: 정답 하나당 1점입니다.
Correct Answer:

Explanation:

AI systems must consistently operate as intended, even under unexpected conditions. = Reliability and safety This description matches the Microsoft responsible AI principle of reliability and safety , which focuses on ensuring that AI systems behave consistently, safely, and as expected, including under unusual or unexpected conditions.
AI systems must protect and secure personal and business information. = Privacy and security This description matches the Microsoft responsible AI principle of privacy and security , which focuses on protecting personal, confidential, and business-sensitive information and preventing unauthorized access or misuse.
QUESTION NO: 6
머신러닝 모델이 인종이나 성별 편견을 보이지 않는다는 것을 검증하는 것은 마이크로소프트의 책임 있는 AI 원칙 중 어떤 원칙에 부합하는 사례입니까?

Correct Answer: B Vote an answer
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QUESTION NO: 7
다음 각 문장에 대해, 문장이 사실이면 '예'를 선택하고, 그렇지 않으면 '아니요'를 선택하십시오.
참고: 정답 하나당 1점입니다.
Correct Answer:

Explanation:

Statement 1: An AI generative model is retrained before performing each user request. = No A generative AI model is not retrained for every user request. During normal use, the model performs inference: it receives input, processes the prompt, and generates a response based on the deployed model.
Statement 2: An AI agent responds by copying and pasting answers stored in a database. = No An AI agent does not simply copy and paste stored answers. Agents use generative AI models, instructions, context, and optionally tools or connected data sources to reason over user input and produce responses or actions.
Statement 3: An AI agent uses a generative AI model to establish actions based on user input. = Yes This is correct. An AI agent uses a generative AI model together with instructions and available tools to interpret user input, determine the next action, and generate a response.
QUESTION NO: 8
귀사는 인공지능(AI) 활용을 위한 모범 사례를 검토하고 있습니다.
각 작업은 마이크로소프트의 책임 있는 AI 원칙 중 어떤 원칙에 해당하는 예시인가요? 정답을 맞추려면 해당 원칙을 올바른 작업으로 드래그하세요. 각 작업은 한 번, 여러 번 또는 전혀 사용되지 않을 수 있습니다. 내용을 보려면 창 사이의 분할 막대를 드래그하거나 스크롤해야 할 수도 있습니다.
참고: 정답 하나당 1점입니다.
Correct Answer:

Explanation:
* Fairness
* Privacy and security
* Transparency
* Reliability and safety
Comprehensive and Detailed Explanation with all Azure AI documents : =
Evaluating model outputs to ensure that decisions are NOT biased against specific demographic groups:
Fairness
Microsoft's responsible AI principle of fairness means AI systems should treat people fairly and avoid unfair bias across demographic groups.
Encrypting sensitive customer data and restricting system access to authorized personnel: Privacy and security The privacy and security principle requires AI systems to protect personal and sensitive data and prevent unauthorized access.
Informing users when they are interacting with an AI system and explaining the system's capabilities and limitations: Transparency The transparency principle requires that people understand when they are interacting with AI and understand the system's purpose, capabilities, and limitations.
Testing AI systems under different conditions to reduce unexpected failures: Reliability and safety The reliability and safety principle means AI systems should operate reliably and safely, including through testing and validation under expected and unexpected conditions.

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