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AIGP시험패스가능한인증공부자료 & AIGP최신버전시험대비자료

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IAPP AIGP 시험요강:

주제
소개

주제 1

Understanding the Foundations of Artificial Intelligence: This topic defines AI and machine learning. It also provides an overview of the different types of AI systems and their use cases.

주제 2

Contemplating Ongoing Issues and Concerns: The topic focuses on issues around AI governance.

주제 3

Understanding How Current Laws Apply to AI Systems: It focuses on laws that govern the use of artificial intelligence.

주제 4

Implementing Responsible AI Governance and Risk Management: It explains the collaboration of major AI stakeholders in a layered approach.

주제 5

Understanding AI Impacts and Responsible AI Principles: This topic identifies different risks that that ungoverned AI systems. The topic also describes features and principles that are essential for trustworthy and ethical AI.

주제 6

Understanding the AI Development Life Cycle: The topic outlines the context in which AI risks are managed.

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최신 Artificial Intelligence Governance AIGP 무료샘플문제 (Q51-Q56):

질문 # 51
An Al system that maintains its level of performance within defined acceptable limits despite real world or adversarial conditions would be described as?

A. Reinforced.
B. Reliable.
C. Resilient.
D. Robust.

정답：C

설명：
An AI system that maintains its level of performance within defined acceptable limits despite real-world or adversarial conditions is described as resilient. Resilience in AI refers to the system's ability to withstand and recover from unexpected challenges, such as cyber-attacks, hardware failures, or unusual input data. This characteristic ensures that the AI system can continue to function effectively and reliably in various conditions, maintaining performance and integrity. Robustness, on the other hand, focuses on the system's strength against errors, while reliability ensures consistent performance over time. Resilience combines these aspects with the capacity to adapt and recover.

질문 # 52
Your organization is searching for a new way to help accurately forecast sales predictions by various types of customers.
Which of the following is the best type of model to choose if your organization wants to customize the model and avoid lock-in?

A. A subscription-based, multimodal model.
B. A classic machine learning model.
C. A proprietary generative AI model.
D. A free large language model.

정답：B

설명：
Forcustomizable, interpretable modelsthat allow organizations toretain control and avoid vendor lock-in, classic ML models(e.g., regression, decision trees, random forests) are optimal.
From theAI Governance in Practice Report 2024:
"Organizations seeking transparency, customizability, and control often prefer classic ML models due to their flexibility and ease of governance." (p. 33)
* AandCmay have limited transparency and are often tied to specific providers.
* Dinvolves ongoing costs and limited model control.

질문 # 53
Which of the following deployments of generative Al best respects intellectual property rights?

A. The system categorizes and applies filters to content based on licensing terms.
B. The system produces content that is modified to closely resemble copyrightedwork.
C. The system provides attribution to creators of publicly available information.
D. The system produces content that includes trademarks and copyrights.

정답：A

설명：
Respecting intellectual property rights means adhering to licensing terms and ensuring that generated content complies with these terms. A system that categorizes and applies filters based on licensing terms ensures that content is used legally and ethically, respecting the rights of content creators. While providing attribution is important, categorization and application of filters based on licensing terms are more directly tied to compliance with intellectual property laws. This principle is elaborated in the IAPP AIGP Body of Knowledge sections on intellectual property and compliance.

질문 # 54
Which of the following steps occurs in the design phase of the Al life cycle?

A. Risk impact estimation.
B. Data augmentation.
C. Model explainability.
D. Performance evaluation.

정답：A

설명：
Risk impact estimation occurs in the design phase of the AI life cycle. This step involves evaluating potential risks associated with the AI system and estimating their impacts to ensure that appropriate mitigation strategies are in place. It helps in identifying and addressing potential issues early in the design process, ensuring the development of a robust and reliable AI system. Reference: AIGP Body of Knowledge on AI Design and Risk Management.

질문 # 55
A US hospital plans to develop an AI that will review available patient data in order to propose an initial diagnosis to licensed physicians. The hospital will implement a policy that requires physicians to consider the AI proposal, but conduct their own physical examinations prior to making a final diagnosis.
An important ethical concern with this plan is?

A. Whether the AI was trained on a representative dataset.
B. Whether the AI will have an error rate comparable to human physicians.
C. Whether patients will receive an economic benefit from the use of AI.
D. Whether physicians understand how the AI works.

정답：A

설명：
The core ethical concern when deploying diagnostic AI in a healthcare setting is ensuringfairness and accuracy across diverse patient populations. If the AI is trained on a dataset that isnot representativeof the population it will serve, it risks reinforcing health disparities and leading to misdiagnoses.
From theAI Governance in Practice Report 2024:
"Training datasets lacking in diversity can produce outputs that systematically underperform for certain groups... this can lead to inaccurate or biased outcomes in healthcare settings." (p. 41)
"Bias, discrimination and fairness challenge... inadequate or nonrepresentative training data can result in AI systems that propagate historical disparities." (p. 42) While physician oversight may reduce risk,biased data can still shape clinical decision-making.
* A- Economic benefit is not central to ethical risk here.
* C- Important but less critical than data representativeness.
* D- Error rate matters but is addressed via validation; it's not the core ethical issue.

질문 # 56
......

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