AIGP試験解説 & AIGP試験復習赤本

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IAPP AIGP 認定試験の出題範囲：

トピック	出題範囲
トピック 1	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.
トピック 2	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.
トピック 3	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.
トピック 4	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.

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AIGP試験復習赤本 & AIGP最新対策問題

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IAPP Certified Artificial Intelligence Governance Professional 認定 AIGP 試験問題 (Q136-Q141):

質問 # 136
A shipping service based in the US is looking to expand its operations into the EU. It utilizes an in-house developed multimodal AI model that analyzes all personal data collected from shipping senders and recipients, and optimizes shipping routes and schedules based on this data. As they expand into the EU, all of the following descriptions should be included in the technical documentation for their AI model EXCEPT:

A. A description of the appropriateness of the performance metrics for the specific AI system.
B. A detailed description of the elements of the AI system and of the process for its development.
C. A general description of the AI system.
D. A description of the prioritization of the risks of deployment of the AI system.

正解：D

解説：
While risk management is important, the EU AI Act requires documenting the AI system's description, performance metrics appropriateness, and detailed technical elements, but not specifically the prioritization of deployment risks in the technical documentation.

質問 # 137
AU.S. mortgage company developed an AI platform that was trained using anonymized details from mortgage applications, including the applicant's education, employment and demographic information, as well as from subsequent payment or default information. The AI platform will be used to automatically grant or deny new mortgage applications, depending on whether the platform views an applicant as presenting a likely risk of default. Which of the following laws is NOT relevant to this use case?

A. Fair Housing Act.
B. Equal Credit Opportunity Act.
C. Fair Credit Reporting Act.
D. Title VII of the Civil Rights Act of 1964.

正解：D

解説：
Title VII of the Civil Rights Act primarily governs employment discrimination and is not directly relevant to mortgage lending decisions, unlike the other listed laws.

質問 # 138
An AI system's function, the industry and the location in which it operates are important factors in considering which of the following?

A. Organizational accountability.
B. Explainability of results.
C. Internal governance needs.
D. Diversity of data sources.

正解：C

解説：
The AI system's function, industry, and operational location influence the internal governance needs necessary to ensure compliance, risk management, and ethical considerations appropriate to the context.

質問 # 139
Under the Canadian Artificial Intelligence and Data Act, when must the Minister of Innovation, Science and Industry be notified about a high-impact Al system?

A. When use of the system causes or is likely to cause material harm.
B. Upon initial deployment of the system.
C. When the algorithmic impact assessment has been completed.
D. Upon release of a new version of the system.

正解：B

解説：
According to the Canadian Artificial Intelligence and Data Act, high-impact AI systems must notify the Minister of Innovation, Science and Industry upon initial deployment. This requirement ensures that the authorities are aware of the deployment of significant AI systems and can monitor their impacts and compliance with regulatory standards from the outset. This initial notification is crucial for maintaining oversight and ensuring the responsible use of AI technologies. Reference: AIGP Body of Knowledge, domain on AI laws and standards.

質問 # 140
CASE STUDY
A company is considering the procurement of an AI system designed to enhance the security of IT infrastructure. The AI system analyzes how users type on their laptops, including typing speed, rhythm and pressure, to create a unique user profile. This data is then used to authenticate users and ensure that only authorized personnel can access sensitive resources.
The data processed by the AI system would be classified as:

A. Organizational data, since it is part of the authentication process
B. Special category data, if it can be used to uniquely identify a person
C. Non-personal data, as long as it is not linked to a user ID
D. Non-sensitive personal data, since it does not reveal information about health, gender or race

正解：B

解説：
The correct answer is D. Keystroke dynamics, used to identify individuals, fall under biometric data, which is a special category of personal data under the GDPR and other frameworks.
From the AI Governance in Practice Report 2024:
"Keystroke dynamics may constitute biometric data if used to uniquely identify an individual... Biometric data is classified as special category personal data and requires higher protection standards." Also reflected in ILT Participant Guide:
"Biometric data, such as facial images, voiceprints, iris scans or keystroke patterns, are treated as special category data when they are used for the purpose of uniquely identifying individuals."

質問 # 141
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