使いやすいAIGP試験復習: IAPP Certified Artificial Intelligence Governance Professionalみんながお進めるAIGP対応内容

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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
  • 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 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 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 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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IAPP Certified Artificial Intelligence Governance Professional 認定 AIGP 試験問題 (Q133-Q138):

質問 # 133
CASE STUDY
Please use the following to answer the next question:
A small local flower delivery company operates a few stores and has a limited IT budget. To reduce the time spent on customer service, which is a major drain on employee time, the company plans to implement a simple but high-performance generative AI chatbot on its website. The chatbot will provide real-time, fact- based responses to customer inquiries and assist with order processing, helping to reduce incoming phone calls.
The company currently uses a single on-premises server for its order database and email system and has not yet partnered with a cloud provider.
An internal data privacy policy governs the use of customer data. This policy, written before the adoption of AI, allows the use or transfer of customer data beyond name and contact information but requires that all such data be deleted after the order is completed. The company prefers to maintain this policy without changes.
MULTI-SELECT
Please select 3 of the 5 options below. No partial credit will be given.
Which of the following actions would necessitate a change to the company ' s privacy policy?

正解：A、B、D

解説：
A, D, and E introduce processing materially different from the practices described in the existing privacy policy. Storing chatbot inputs for RAG creates an additional retention and reuse purpose that should be addressed through appropriate privacy disclosures and retention controls. Using customer-session information to retrain the underlying model creates a distinct secondary purpose beyond processing an order, even when the data is subsequently deleted. Scanning a customer ' s appearance to infer frustration or confusion introduces an entirely new category of observation and inference, requiring additional transparency, legal- basis analysis, proportionality assessment, and safeguards. By contrast, B involves transferring customer information to a service provider so the requested service can operate, which the existing policy already permits. C involves ordinary contact and delivery information retained through completion of the transaction, which also fits the stated policy.


質問 # 134
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：D

解説：
According to the GDPR, individuals have the right to not be subject to a decision based solely on automated processing, including profiling, which produces legal effects or similarly significantly affects them. However, there are exceptions to this right, one of which is when the decision is based on the data subject's explicit consent. This means that if an individual explicitly consents to the automated decision-making process, there is no requirement for human intervention to confirm or replace the decision. This exception ensures that individuals can have control over automated decisions that affect them, provided they have given clear and informed consent.


質問 # 135
CASE STUDY
Please use the following to answer the next question:
A mid-size US healthcare network has decided to develop an AI solution to detect a type of cancer that is most likely to 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 to a radiologist for secondary review pursuant to agreed-upon criteria (e.g., a confidence score below a threshold).
To date, the healthcare network has:
- Defined its AI ethical principles.
- Conducted discovery to identify the intended uses and success
criteria for the system.
- Established an AI risk committee.
- Assembled a cross-functional team with clear roles and
responsibilities.
- 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. It also intends to retain a large consulting firm to supplement its small data science team and 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?

正解：D

解説：
The healthcare network's data science team is most important in selecting the specific algorithm type, as they possess the technical expertise and understanding of the data and clinical context required for this decision.


質問 # 136
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?

正解：D

解説：
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.


質問 # 137
The best method to ensure a comprehensive identification of risks for a new AI model is?

正解：D

解説：
The most comprehensive way to identify a full range of risks - legal, ethical, operational, and societal - for a new AI model is through aformal impact assessment, such as aData Protection Impact Assessment (DPIA)orAlgorithmic Impact Assessment.
From theAI Governance in Practice Report 2024:
"Risk-based approaches are often distilled into organizational risk management efforts, which put impact assessments at the heart of deciding whether harm can be reduced." (p. 29)
"DPIAs... help organizations identify, analyze and minimize data-related risks and demonstrate accountability." (p. 30)
* A. Environmental scanis too general.
* B. Red teamingis useful for adversarial risk but not broad.
* C. Integration testingfocuses on technical/system compatibility, not overall risk.


質問 # 138
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