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AIGP合格記 & AIGP受験内容

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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

法律、標準、フレームワークがAIにどのように適用されるかを理解する：この試験セクションでは、コンプライアンス担当者のスキルを評価し、既存および新規の法的要件をAIシステムに適用する方法を網羅します。データプライバシー法、知的財産法、差別禁止法、消費者保護法、製造物責任法がAIにどのような影響を与えるかを考察します。また、EU AI法の主要要素（リスク分類、AIリスクレベルごとの要件、執行メカニズムなど）についても検証します。さらに、OECD原則、NIST AIリスク管理フレームワーク、ISO AI標準などの主要な業界標準とフレームワークを取り上げ、組織が信頼性とコンプライアンスに準拠したAIを実装できるよう導きます。

トピック 2

AIガバナンスの基礎を理解する：このセクションでは、AIガバナンスの専門家のスキルを測定し、AIとは何か、ガバナンスが必要な理由、AIに関連するリスクと固有の特性など、AIガバナンスの中核概念を網羅します。また、役割の定義、部門横断的なコラボレーションの促進、AI戦略に関するトレーニングの実施など、AIガバナンスに対する組織の期待の確立と伝達についても取り上げます。さらに、サードパーティのリスク管理、プライバシーとセキュリティの実践の更新など、AIライフサイクル全体にわたる監視と説明責任を確保するためのポリシーと手順の策定にも重点を置いています。

トピック 3

AIの導入と利用を統制する方法の理解：この試験セクションでは、テクノロジー導入リーダーのスキルを評価し、AIモデルを責任ある方法で選択、導入、利用することに関連する責任を網羅します。導入前に主要な要因とリスクを評価すること、さまざまなモデルの種類と導入オプションを理解すること、継続的な監視とメンテナンスを確保することなどが含まれます。この分野は、自社開発およびサードパーティのAIモデルの両方に適用され、モデルの運用期間全体にわたる透明性、倫理的配慮、継続的な監視の重要性を強調しています。

トピック 4

AI開発のガバナンス方法の理解：このセクションでは、AIプロジェクトマネージャーのスキルを評価し、AIモデルの設計、構築、トレーニング、テスト、保守に関わるガバナンス責任を網羅します。ビジネスコンテキストの定義、影響評価の実施、関連法規とベストプラクティスの適用、モデル開発中のリスク管理に重点を置いています。また、トレーニングとテストのためのデータガバナンスの確立、データの品質と出所の確保、コンプライアンスプロセスの文書化も含まれます。さらに、リリースに向けたモデルの準備、継続的な監視、保守、インシデント管理、利害関係者への透明性のある情報開示にも重点を置いています。

>> AIGP合格記 <<

AIGP受験内容、AIGP最新試験情報

私はあなたがAIGP試験に合格したいことを知っています。私たちのAIGP学習教材は、多くの人が試験に合格するのを助け、あなたを助けようと思います。私たちのAIGP学習教材の99％の合格率は高いです。また、あなたの自分の努力が必要です。そして、私たちのAIGP試験問題を利用すれば、あなたは絶対試験に合格できます。

IAPP Certified Artificial Intelligence Governance Professional 認定 AIGP 試験問題 (Q20-Q25):

質問 # 20
A UK company has designed a facial recognition model to support border control.
The EU AI Act would apply to the model in all of the following situations EXCEPT if?

A. The model was trained by an EU company.
B. The model was released under an open source license.
C. The model is deployed at an EU border checkpoint.
D. The model is deployed at UK border checkpoints.

正解：D

解説：
TheEU AI Actapplies extraterritorially, meaning it affects entitiesoutside the EUwhen their AI systems impact individuals within the EU. However, it doesnotapply to systems that are developed, sold, or used entirely outside of the EU-such as in theUK, unless they affect the EU market or individuals.
From theAI Governance in Practice Report 2024:
"The act imposes regulatory obligations... depending on their capabilities, reach and computing power, certain GPAI systems are considered to present systemic risk and attract broadly similar obligations to those applicable to high-risk AI systems." (p. 7)
"The EU AI Act is the world's first comprehensive AI regulation... requirements apply to providers, deployers, importers, and distributors of AI systems when such systems are placed on the EU market." (p. 7-8) Thus:
* A. Open source releasedoes not exclude applicability if deployed in the EU.
* B. Deployment at an EU borderclearly invokes jurisdiction.
* D. Training by an EU companycreates jurisdictional links.
* C. Deployment only at UK checkpoints, withno EU use or impact, isoutside scope.

質問 # 21
CASE STUDY
Please use the following answer the next question:
A local police department in the United States procured an Al system to monitor and analyze social media feeds, online marketplaces and other sources of public information to detect evidence of illegal activities (e.g., sale of drugs or stolen goods). The Al system works by surveilling the public sites in order to identify individuals that are likely to have committed a crime. It cross-references the individuals against data maintained by law enforcement and then assigns a percentage score of the likelihood of criminal activity based on certain factors like previous criminal history, location, time, race and gender.
The police department retained a third-party consultant assist in the procurement process, specifically to evaluate two finalists. Each of the vendors provided information about their system's accuracy rates, the diversity of their training data and how their system works. The consultant determined that the first vendor's system has a higher accuracy rate and based on this information, recommended this vendor to the police department.
The police department chose the first vendor and implemented its Al system. As part of the implementation, the department and consultant created a usage policy for the system, which includes training police officers on how the system works and how to incorporate it into their investigation process.
The police department has now been using the Al system for a year. An internal review has found that every time the system scored a likelihood of criminal activity at or above 90%, the police investigation subsequently confirmed that the individual had, in fact, committed a crime. Based on these results, the police department wants to forego investigations for cases where the Al system gives a score of at least 90% and proceed directly with an arrest.
The best human oversight mechanism for the police department to implement is that a police officer should?

A. Consider the Al recommendation as part of the criminal investigation.
B. Ensure an accused is given notice that the Al system was used.
C. Confirm the Al recommendation prior to sentencing.
D. Explain to the accused how the Al system works.

正解：A

解説：
The best human oversight mechanism for the police department to implement is for a police officer to consider the AI recommendation as part of the criminal investigation. This ensures that the AI system's output is used as a tool to aid human decision-making rather than replace it. The police officer should integrate the AI's insights with other evidence and contextual information to make informed decisions, maintaining a balance between technological aid and human judgment. Reference: AIGP Body of Knowledge on AI Integration and Human Oversight.

質問 # 22
Which type of existing assessment could best be leveraged to create an Al impact assessment?

A. A privacy impact assessment.
B. A security impact assessment.
C. A safety impact assessment.
D. An environmental impact assessment.

正解：A

解説：
A privacy impact assessment (PIA) can be effectively leveraged to create an AI impact assessment. A PIA evaluates the potential privacy risks associated with the use of personal data and helps in implementing measures to mitigate those risks. Since AI systems often involve processing large amounts of personal data, the principles and methodologies of a PIA are highly applicable and can be extended to assess broader impacts, including ethical, social, and legal implications of AI. Reference: AIGP Body of Knowledge on Impact Assessments.

質問 # 23
CASE STUDY
Please use the following answer the next question:
ABC Corp, is a leading insurance provider offering a range of coverage options to individuals. ABC has decided to utilize artificial intelligence to streamline and improve its customer acquisition and underwriting process, including the accuracy and efficiency of pricing policies.
ABC has engaged a cloud provider to utilize and fine-tune its pre-trained, general purpose large language model ("LLM"). In particular, ABC intends to use its historical customer data-including applications, policies, and claims-and proprietary pricing and risk strategies to provide an initial qualification assessment of potential customers, which would then be routed tA. human underwriter for final review.
ABC and the cloud provider have completed training and testing the LLM, performed a readiness assessment, and made the decision to deploy the LLM into production. ABC has designated an internal compliance team to monitor the model during the first month, specifically to evaluate the accuracy, fairness, and reliability of its output. After the first month in production, ABC realizes that the LLM declines a higher percentage of women's loan applications due primarily to women historically receiving lower salaries than men.
The best approach to enable a customer who wants information on the Al model's parameters for underwriting purposes is to provide?

A. A transparency notice.
B. Detailed terms of service.
C. An opt-out mechanism.
D. Customer service support.

正解：A

解説：
The best approach to enable a customer who wants information on the AI model's parameters for underwriting purposes is to provide a transparency notice. This notice should explain the nature of the AI system, how it uses customer data, and the decision-making process it follows. Providing a transparency notice is crucial for maintaining trust and compliance with regulatory requirements regarding the transparency and accountability of AI systems.
Reference: According to the AIGP Body of Knowledge, transparency in AI systems is essential to ensure that stakeholders, including customers, understand how their data is being used and how decisions are made. This aligns with ethical principles of AI governance, ensuring that customers are informed and can make knowledgeable decisions regarding their interactions with AI systems.

質問 # 24
After deploying an AI model, what must be documented?

A. The model's architecture, performance metrics and updates.
B. Encountered issues, the monitoring process and risks.
C. Licensing information, the team and business goals.
D. The data used to train, hyperparameters and stakeholder feedback.

正解：A

解説：
Documentation must include the model's architecture, performance metrics, and updates to ensure transparency, reproducibility, and ongoing maintenance.

質問 # 25
......

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受験内容: https://www.shikenpass.com/AIGP-shiken.html

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