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AIGP試験の準備方法｜最高のAIGPトレーリング学習試験｜最新のIAPP Certified Artificial Intelligence Governance Professional試験概要

P.S.ShikenPASSがGoogle Driveで共有している無料の2025 IAPP AIGPダンプ：https://drive.google.com/open?id=1uVUp2gIEk8uaM-wVWC8D_R6UZSjthc-Q

弊社のIAPPのAIGP試験問題集を買うかどうかまだ決めていないなら、弊社のデモをやってみよう。使用してから、あなたは弊社の商品でIAPPのAIGP試験に合格できるということを信じています。我々ShikenPASSの専門家たちのIAPPのAIGP試験問題集への更新と改善はあなたに試験の準備期間から成功させます。

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 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.

トピック 2

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 3

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 4

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.

>> AIGPトレーリング学習 <<

AIGP試験概要 & AIGP技術内容

AIGPテストガイドは、時間の無駄を避けるために、できるだけ早くこれらの資料を学習できることを保証できます。 IAPP Certified Artificial Intelligence Governance Professional Study Questionは、不明瞭な概念を簡素化することにより、学習方法を最適化するのに役立ちます。 AIGP試験問題は、アフターサービスを完璧にするための努力をspareしみません。

IAPP Certified Artificial Intelligence Governance Professional 認定 AIGP 試験問題 (Q112-Q117):

質問 # 112
Under the NIST Al Risk Management Framework, all of the following are defined as characteristics of trustworthy Al EXCEPT?

A. Secure and Resilient.
B. Explainable and Interpretable.
C. Accountable and Transparent.
D. Tested and Effective.

正解：D

解説：
The NIST AI Risk Management Framework outlines several characteristics of trustworthy AI, including being secure and resilient, explainable and interpretable, and accountable and transparent. While being tested and effective is important, it is not explicitly listed as a characteristic of trustworthy AI in the NIST framework.
The focus is more on the system's ability to function safely, securely, and transparently in a way that stakeholders can understand and trust. Reference: AIGP Body of Knowledge, NIST AI RMF section.

質問 # 113
Why is it important that conformity requirements are satisfied before an AI system is released into production?

A. To guarantee interoperability of the AI system across multiple platforms and environments.
B. To comply with legal and regulatory standards, ensuring the AI system is safe and trustworthy.
C. To ensure the visual design is fit-for-purpose.
D. To ensure the AI system is easy for end-users to operate.

正解：B

解説：
Conformity assessmentsare a core requirement under theEU AI Actfor high-risk systems and serve to confirm that the AI meetsregulatory, safety, and ethical standardsbefore it is put into production.
From theAI Governance in Practice Report 2024:
"Conformity assessments... ensure that systems comply with legal requirements, safety criteria, and intended purpose before being placed on the market." (p. 34)
"They are a critical step to demonstrate safety and trustworthiness in AI deployment." (p. 35)

質問 # 114
A company developed Al technology that can analyze text, video, images and sound to tag content, including the names of animals, humans and objects.
What type of Al is this technology classified as?

A. Expert system.
B. Multi-modal model.
C. Transformative Al.
D. Deductive inference.

正解：B

解説：
A multi-modal model is an AI system that can process and analyze multiple types of data, such as text, video, images, and sound. This type of AI integrates different data sources to enhance its understanding and decision-making capabilities. In the given scenario, the AI technology that tags content including names of animals, humans, and objects falls under this category. Reference: AIGP BODY OF KNOWLEDGE, which outlines the capabilities and use cases of multi-modal models.

質問 # 115
Retrieval-Augmented Generation (RAG) is defined as?

A. Fine tuning LLMs to minimize biased outputs.
B. Reducing computational processing requirements of the LLMs.
C. Applying advanced filtering techniques to the LLMs.
D. Combining LLMs with private knowledge bases to improve their outputs.

正解：D

解説：
Retrieval-Augmented Generation (RAG)enhances Large Language Models (LLMs) by integratingexternal, up-to-date, or proprietary informationinto the generation pipeline-allowing the model tofetch relevant factsfrom a trusted knowledge source at query time.
Though RAG is not defined directly in the IAPP documents, it is a widely recognized technique in AI governance for ensuringmore accurate and contextually grounded outputs, especially inregulated or high- stakes environmentswhere hallucinations are a concern.
* B, C, and Ddescribe optimization or bias mitigation-not the core function of RAG.

質問 # 116
When monitoring the functional performance of a model that has been deployed into production, all of the following are concerns EXCEPT?

A. Feature drift.
B. Data loss.
C. Model drift.
D. System cost.

正解：D

解説：
When monitoring the functional performance of a model deployed into production, concerns typically include feature drift, model drift, and data loss. Feature drift refers to changes in the input features that can affect the model's predictions. Model drift is when the model's performance degrades over time due to changes in the data or environment. Data loss can impact the accuracy and reliability of the model. However, system cost, while important for budgeting and financial planning, is not a direct concern when monitoring the functional performance of a deployed model. Reference: AIGP Body of Knowledge on Model Monitoring and Maintenance.

質問 # 117
......

AIGPテストの質問には、PDFバージョン、PCバージョン、APPオンラインバージョンなど、3つのバージョンがあります。また、AIGPテスト資料ユーザーは、自分の好みに応じて選択できます。最も人気のあるバージョンは、AIGP試験準備のPDFバージョンです。 PDFバージョンのAIGPテスト問題を印刷して、いつでもどこでも学習できるようにしたり、自分の優先事項を学習したりできます。 AIGP試験準備のPCバージョンは、Windowsユーザー向けです。 APPオンラインバージョンを使用する場合は、アプリケーションプログラムをダウンロードするだけで、AIGPテスト資料サービスをお楽しみいただけます。

AIGP試験概要: https://www.shikenpass.com/AIGP-shiken.html