AIGP試験の準備方法｜信頼的なAIGP合格率試験｜有難いIAPP Certified Artificial Intelligence Governance Professional日本語版問題集

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IAPP AIGP Exam Syllabus Topics:

SectionObjectives
AI Risk Management- Risk Frameworks and Standards
  • 1. ISO 31000 Risk Management
  • 2. NIST AI Risk Management Framework (RMF)
- Operationalizing Risk Management
  • 1. Risk mitigation strategies
  • 2. Risk identification and assessment
AI Governance Implementation- Organizational Governance
  • 1. Governance Structures
  • 2. Roles and Responsibilities (RACI)
  • 3. Policies and Procedures
- Data Governance for AI
  • 1. Data Privacy and Protection
  • 2. Data Quality and Integrity
AI Laws, Regulations, and Standards- Global AI Frameworks
  • 1. UNESCO AI Ethics
  • 2. OECD AI Principles
  • 3. ISO/IEC Standards
- Regional and National Regulations
  • 1. US State and Federal Regulations
  • 2. EU AI Act
  • 3. National AI Strategies
AI Governance Management- Emerging Issues
  • 1. Future Trends
  • 2. Ethical AI
  • 3. Generative AI
- Life Cycle Management
  • 1. Third-party management
  • 2. Auditing and Monitoring
  • 3. Incident Management
Foundations of AI Governance- AI Governance Fundamentals
  • 1. Understanding the AI Development Life Cycle
  • 2. Defining AI and its different approaches
  • 3. Key AI Terminology and Concepts
- Impacts of AI
  • 1. Benefits of AI
  • 2. Risks of AI

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IAPP Certified Artificial Intelligence Governance Professional 認定 AIGP 試験問題 (Q213-Q218):

質問 # 213
All of the following are unique characteristics of AI that require a comprehensive approach to governance EXCEPT: (Choose three.)

正解：A、B、D

解説：
The commonly recognized unique characteristics of AI that drive the need for comprehensive governance are autonomy and adaptability.
Automation, speed and scale, and superintelligence are not considered core unique characteristics for governance purposes in standard AI governance frameworks, making them the correct exceptions.


質問 # 214
Who is responsible for ongoing maintenance and monitoring of an AI system after it has been put into production?

正解：C

解説：
The deployer is primarily responsible for operational oversight once an AI system has been placed into use within its organization. This includes monitoring performance, identifying drift or unexpected behavior, following the provider's instructions, escalating incidents, and ensuring that the system continues to operate within approved risk tolerances. Under Article 26 of the EU AI Act, deployers of high-risk AI systems are specifically required to monitor system operation based on the instructions for use and to inform the provider and relevant authorities when serious risks or incidents arise. Developers and providers remain responsible for important lifecycle activities such as design, documentation, updates, and technical support, but ongoing monitoring in the actual deployment environment rests principally with the deployer. A regulator provides external oversight, while an ordinary user does not carry organizational lifecycle responsibility.


質問 # 215
Which of the following Al uses is best described as human-centric?

正解：B

解説：
Human-centric AI focuses on improving the human experience by addressing individual needs and enhancing human capabilities. Option D exemplifies this by using virtual assistants to tailor educational content to each student's unique abilities and needs, thereby supporting personalized learning and improving educational outcomes. This use case directly benefits individuals by providing customized assistance and adapting to their learning pace and style, aligning with the principles of human-centric AI.


質問 # 216
Why must AI governance policies address third-party AI systems?

正解：A


質問 # 217
CASE STUDY
Please use the following to answer the next question:
You have recently assumed the role of AI Governance leader for a California-based medical technology company. The organization primarily serves hospitals and has recently expanded to include walk-in clinics located within local pharmacies.
The company ' s core business focuses on diagnostic assistance powered by a large language model LLM and back-office process optimization using Agentic AI, including chatbots, medical record request handling, scheduling and billing.
In preparation for its next round of funding, the board has asked you to prepare an AI Risk report to demonstrate to investors how the company is addressing AI-related risks. In preparing the report you learn that last year the company generated 30 million dollars in gross revenue across the US, EU, India, and South Korea and that vendors are engaged for various activities, including model testing and providing third-party AI solutions for chatbots.
Which of the following best exemplifies human oversight capabilities you should enable under the relevant AI laws?

正解：A

解説：
The correct answer is A because it directly demonstrates meaningful human oversight over AI-generated outcomes, which is a key requirement in AI governance frameworks and regulations such as the EU AI Act.
Human oversight requires that a qualified human can review, intervene, and override AI decisions before they produce legal or significant real-world effects. In high-risk contexts like healthcare diagnostics, governance frameworks emphasize "human-in-the-loop" controls to prevent harm and ensure accountability. Option A ensures a licensed medical professional validates the AI output before it is finalized, aligning with safety, accountability, and risk mitigation principles. Other options describe training, system design, or monitoring, which are important governance measures but do not constitute direct oversight of individual AI decisions at the point of impact, making them insufficient under strict regulatory expectations.


質問 # 218
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