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IAPP AIGP 시험요강:

주제	소개
주제 1	Understanding How to Govern AI Deployment and Use: This section of the exam measures skills of technology deployment leads and covers the responsibilities associated with selecting, deploying, and using AI models in a responsible manner. It includes evaluating key factors and risks before deployment, understanding different model types and deployment options, and ensuring ongoing monitoring and maintenance. The domain applies to both proprietary and third-party AI models, emphasizing the importance of transparency, ethical considerations, and continuous oversight throughout the model’s operational life.
주제 2	Understanding How Laws, Standards, and Frameworks Apply to AI: This section of the exam measures skills of compliance officers and covers the application of existing and emerging legal requirements to AI systems. It explores how data privacy laws, intellectual property, non-discrimination, consumer protection, and product liability laws impact AI. The domain also examines the main elements of the EU AI Act, such as risk classification and requirements for different AI risk levels, as well as enforcement mechanisms. Furthermore, it addresses the key industry standards and frameworks, including OECD principles, NIST AI Risk Management Framework, and ISO AI standards, guiding organizations in trustworthy and compliant AI implementation.
주제 3	Understanding How to Govern AI Development: This section of the exam measures the skills of AI project managers and covers the governance responsibilities involved in designing, building, training, testing, and maintaining AI models. It emphasizes defining the business context, performing impact assessments, applying relevant laws and best practices, and managing risks during model development. The domain also includes establishing data governance for training and testing, ensuring data quality and provenance, and documenting processes for compliance. Additionally, it focuses on preparing models for release, continuous monitoring, maintenance, incident management, and transparent disclosures to stakeholders.
주제 4	Understanding the Foundations of AI Governance: This section of the exam measures skills of AI governance professionals and covers the core concepts of AI governance, including what AI is, why governance is needed, and the risks and unique characteristics associated with AI. It also addresses the establishment and communication of organizational expectations for AI governance, such as defining roles, fostering cross-functional collaboration, and delivering training on AI strategies. Additionally, it focuses on developing policies and procedures that ensure oversight and accountability throughout the AI lifecycle, including managing third-party risks and updating privacy and security practices.

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최신 Artificial Intelligence Governance AIGP 무료샘플문제 (Q11-Q16):

질문 # 11
CASE STUDY
Please use the following answer the next question:
A mid-size US healthcare network has decided to develop an Al solution to detect a type of cancer that is most likely arise in adults. Specifically, the healthcare network intends to create a recognition algorithm that will perform an initial review of all imaging and then route records a radiologist for secondary review pursuant agreed-upon criteria (e.g., a confidence score below a threshold).
To date, the healthcare network has taken the following steps: defined its Al ethical principles: conducted discovery to identify the intended uses and success criteria for the system: established an Al governance committee; assembled a broad, crossfunctional team with clear roles and responsibilities; and created policies and procedures to document standards, workflows, timelines and risk thresholds during the project.
The healthcare network intends to retain a cloud provider to host the solution and a consulting firm to help develop the algorithm using the healthcare network's existing data and de-identified data that is licensed from a large US clinical research partner.
Which stakeholder group is most important in selecting the specific type of algorithm?

A. The cloud provider.
B. The consulting firm.
C. The healthcare network'sdata science team.
D. The healthcare network's Al governance committee.

정답：C

설명：
In selecting the specific type of algorithm for the AI solution, the healthcare network's data science team is most important. This team possesses the technical expertise and understanding of the data, the clinical context, and the performance requirements needed to make an informed decision about which algorithm is most suitable. While the cloud provider and consulting firm can offer support and infrastructure, and the AI governance committee provides oversight, the data science team's specialized knowledge is crucial for selecting and implementing the appropriate algorithm. Reference: AIGP Body of Knowledge, AI governance and team roles section.

질문 # 12
After initially deploying a third-party AI model, you learn the developer has released a new version.
As deployer of this third-party model, what should you do?

A. Seek input from data scientists.
B. Retrain the model.
C. Audit the model.
D. Communicate necessary updates to your users.

정답：C

설명：
When anew versionof a third-party model is released, the deployer must ensure it still meets safety, performance, and compliance requirements - which calls for aformal audit.
From theAI Governance in Practice Report 2024:
"Any updates or changes to AI systems should trigger a re-evaluation to ensure continued compliance and performance." (p. 12)
"Post-market monitoring includes reassessing the impact of updated models or retraining." (p. 35)

질문 # 13
Scenario:
A distributor operating in the EU is responsible for selling imported high-risk AI systems to businesses. The distributor wants to ensure they fulfill all applicable obligations under the EU AI Act.
All of the following are obligations of a distributor of high-risk AI systems under the EU AI Act EXCEPT?

A. Communication with national authorities
B. Corrective actions
C. Registration in EU Database
D. Verification of CE marking

정답：C

설명：
The correct answer is C. Registration in the EU database is an obligation of providers of high-risk AI systems-not distributors.
From the AIGP ILT Guide - Roles & Obligations Module:
"Distributors must verify CE marking, ensure instructions for use are provided, inform authorities of risks, and take corrective action when necessary. However, registration duties in the EU database lie with the provider." Also from the AI Governance in Practice Report 2024:
"The AI Act differentiates responsibilities for developers, providers, importers, and distributors. Only providers of high-risk systems are obligated to register their systems in the EU AI Database." Distributors focus on verification and communication, not formal registration.

질문 # 14
Scenario:
A company is using different types of AI systems to enhance consumer engagement. These include chatbots, recommendation engines, and automated content generation tools.
Which of the following situations would be least likely to raise concerns under existing consumer protection laws?

A. An AI algorithm being used in a credit decision-making process by a financial institution
B. An AI tool using scraped digital content to generate news summaries on a publishing website
C. An AI customer service system claiming that it is as accurate as a human support agent
D. An online platform offering recommendations to its users by displaying user-specific content and targeted advertisements

정답：D

설명：
The correct answer is D. Personalized content and advertisements, as long as properly disclosed and non- deceptive, are not generally a consumer protection issue under current legal regimes.
From the AI Governance in Practice Report 2024 (Consumer Protection Section):
"Standard practices like targeted advertising and recommendations are widely accepted provided they comply with transparency and consent requirements." Meanwhile, credit decision-making and misleading AI performance claims (Answers A and B) have already led to regulatory enforcement.
The AIGP ILT Guide highlights:
"Deceptive claims, biased financial decisions, and unauthorized data use may violate consumer protection and privacy laws. Advertising personalization is routine but must be disclosed appropriately."

질문 # 15
Scenario:
An organization wants to leverage its existing compliance structures to identify AI-specific risks as part of an ongoing data governance audit.
Which of the following compliance-related controls within an organization is most easily adapted to identify AI risks?

A. Penetration testing
B. Privacy impact assessments
C. Privacy training
D. Transfer risk assessments

정답：B

설명：
The correct answer is D - Privacy impact assessments (PIAs). These are directly adaptable for identifying risks in AI systems, particularly around data usage, bias, and individual impacts.
From the AIGP ILT Guide - Risk Management Module:
"PIAs and DPIAs are existing tools used in privacy compliance that can be extended to evaluate the risks of AI, including fairness, explainability, and legality." AI Governance in Practice Report 2024 further explains:
"Organizations can adapt privacy impact assessments to evaluate the ethical, legal, and technical risks posed by AI systems. They provide a structured and recognized method." PIAs are preferable over general security practices (like pen testing) which do not address algorithmic bias or legal compliance directly.

질문 # 16
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