IAPP AIGP Exam | AIGP日本語認定対策 -準備を助けるAIGP試験効率

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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 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 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.

>> AIGP日本語認定対策 <<

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IAPP Certified Artificial Intelligence Governance Professional 認定 AIGP 試験問題 (Q10-Q15):

質問 # 10
According to the GDPR, an individual has the right to have a human confirm or replace an automated decision unless that automated decision:

正解:A

解説:
GDPR permits automated decisions without human intervention if authorized by EU law and accompanied by appropriate safeguards protecting the individual's rights.


質問 # 11
Scenario:
A mid-sized tech firm is building its AI governance program and is exploring ISO/IEC standards that could support consistency in terminology and risk assessment processes across teams.
ISO/IEC 22989 and ISO/IEC 42001 can be valuable resources for AI Governance professionals in all of the following ways EXCEPT:

正解:C

解説:
The correct answer is C. ISO/IEC 22989 and 42001 focus on terminology, risk, and management systems, but do not specifically address procurement-related concerns with third-party vendors.
From the AIGP Body of Knowledge - Standards Section:
"ISO/IEC 22989 defines terminology and foundational concepts. ISO/IEC 42001 provides a management system standard for AI. They are not procurement-focused documents." Also confirmed in the AI Governance in Practice Report 2024:
"These standards help establish common language and risk governance procedures. Procurement governance typically falls under separate frameworks or sector-specific guidance." Thus, procurement governance (Option C) is not a central use case for these standards.


質問 # 12
What is the primary purpose of conducting ethical red-teaming on an Al system?

正解:D

解説:
The primary purpose of conducting ethical red-teaming on an AI system is to simulate model risk scenarios.
Ethical red-teaming involves rigorously testing the AI system to identify potential weaknesses, biases, and vulnerabilities by simulating real-world attack or failure scenarios. This helps in proactively addressing issues that could compromise the system's reliability, fairness, and security. Reference: AIGP Body of Knowledge on AI Risk Management and Ethical AI Practices.


質問 # 13
A company that deploys AI but is not currently a provider or developer intends to develop and market its own AI system.
Which obligation would then be likely to apply?

正解:B

解説:
Once a company moves from being adeployerto also acting as aprovider or developer, it assumesnew obligationsunder regulations like the EU AI Act. One of the core requirements for providers is to produce and maintaintechnical documentation, including descriptions of the model, associated risks, and mitigation strategies.
From theAI Governance in Practice Report2025:
"Providers of high-risk AI systems must draw up technical documentation demonstrating the system's conformity with the requirements... including potential risks and safeguards applied." (p. 34)
"This documentation must be available before placing the system on the market." (p. 35)


質問 # 14
According to November 2023 White House Executive Order, which of the following best describes the guidance given to governmental agencies on the use of generative Al as a workplace tool?

正解:C

解説:
The November 2023 White House Executive Order provides guidance that governmental agencies should limit access to specific uses of generative AI. This means that generative AI tools should be used in a controlled manner, where their applications are restricted to well-defined, approved use cases that ensure the security, privacy, and ethical considerations are adequately addressed. This approach allows for the benefits of generative AI to be harnessed while mitigating potential risks and abuses.
Reference: AIGP BODY OF KNOWLEDGE, sections on AI governance and risk management, and the White House Executive Order of November 2023.


質問 # 15
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