AIGP問題集で2026年最新のIAPP AIGP試験問題
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質問 # 46
The best practice to manage third-party risk associated with AI systems is to create and implement policies that?
- A. Provide for an appropriate level of due diligence and ongoing monitoring based on the defined risk.
- B. Focus on the technical aspects of AI systems, such as data security, while ethical risks are addressed through suitable contracts.
- C. Focus on the financial stability of third-party vendors as the primary criterion for risk assessment.
- D. Require third-party AI systems to undergo a comprehensive audit by an external cybersecurity firm every six months.
正解：A
解説：
Third-party risk management for AI systems should beproportional and risk-based, involvinginitial due diligenceandongoing monitoringthat reflects thelevel of risk posedby the third party's AI system.
From theAI Governance in Practice Report 2024:
"Third-party due diligence assessments to identify possible external risk and inform selection." (p. 11)
"Legal due diligence may include verification of the personal data's lawful collection by the data broker, review of contractual obligations..." (p. 19)
* Afocuses too narrowly on financial stability.
* Cis excessive and not scalable or aligned with best practices.
* Dinappropriately separates ethical and technical risks; both must be evaluated holistically.
質問 # 47
According to the EU Al Act, providers of what kind of machine learning systems will be required to register with an EU oversight agency before placing their systems in the EU market?
- A. Al systems trained on sensitive personal data.
- B. Al systems that are harmful based on a legal risk-utility calculation.
- C. Al systems that are "strong" general intelligence.
- D. Al systems that are high-risk.
正解：D
解説：
According to the EU AI Act, providers of high-risk AI systems are required to register with an EU oversight agency before these systems can be placed on the market. This requirement is part of the Act's framework to ensure that high-risk AI systems comply with stringent safety, transparency, and accountability standards.
High-risk systems are those that pose significant risks to health, safety, or fundamental rights. Registration with oversight agencies helps facilitate ongoing monitoring and enforcement of compliance with the Act's provisions. Systems categorized under other criteria, such as those trained on sensitive personal data or exhibiting "strong" general intelligence, also fall under scrutiny but are primarily covered under different regulatory requirements or classifications.
質問 # 48
A US-based mortgage lender has purchased a chatbot. They plan to have the chatbot collect information from consumers who are interested in loans and offer the consumers 2-3 different options based on its current pricing and product offerings, which change frequently. This chatbot was initially developed and previously deployed by a Russian airline for booking flights.
The best option for the part of the process that generates the loan offers is?
- A. Quantum computing
- B. Retrieval-Augmented Generation.
- C. Expert System.
- D. Multimodal Generative AI.
正解：C
解説：
Offeringloan products based on current offerings and rulesrequires a system that can followexplicit business logic, not generate open-ended content. Anexpert system, which is a rules-based AI that uses "if- then" logic, is ideal here.
From the AI governance context:
"Rule-based AI systems are often preferred when decisions must adhere to precise regulatory or financial criteria." (aligned with AI best practices in regulated sectors)
* A. RAGis used to integrate external knowledge-not suitable for structured, rule-based logic.
* B. Multimodal modelshandle varied input types-not needed here.
* D. Quantum computingis not yet practical or relevant for this business use case.
質問 # 49
What is the most important reason for documenting risks when developing an AI system?
- A. To provide transparency to stakeholders.
- B. To mitigate potential liability.
- C. To promote knowledge sharing.
- D. To align with industry standards.
正解：B
解説：
The most critical reason for documenting AI-related risks is toreduce exposure to legal, regulatory, and reputational liabilities. Clear documentation demonstrates thatrisks were identified, assessed, and addressed, which is essential for accountability and defensibility in the face of audits, litigation, or enforcement actions.
From theAI Governance in Practice Report 2024:
"An effective AI governance model is about collective responsibility... which should encompass oversight mechanisms such as privacy, accountability, compliance." (p. 13)
"Accountability... is based on the idea that there should be a person or entity that is ultimately responsible for any harm resulting from the use of the data, algorithm and AI system's underlying processes." (p. 28) While transparency, alignment with standards, and knowledge sharing are all secondary benefits,risk documentation's primary role is liability mitigation.
質問 # 50
All of the following may be permissible uses of an Al system under the EU Al Act EXCEPT?
- A. To manage border control.
- B. To promote equitable distribution of welfare benefits.
- C. To implement social scoring.
- D. To detect an individual's intent for law enforcement purposes.
正解：C
解説：
The EU AI Act explicitly prohibits the use of AI systems for social scoring by public authorities, as it can lead to discrimination and unfair treatment of individuals based on their social behavior or perceived trustworthiness. While AI can be used to promote equitable distribution of welfare benefits, manage border control, and even detect an individual's intent for law enforcement purposes (within strict regulatory and ethical boundaries), implementing social scoring systems is not permissible under the Act due to the significant risks to fundamental rights and freedoms.
質問 # 51
What is the best method to proactively train an LLM so that there is mathematical proof that no specific piece of training data has more than a negligible effect on the model or its output?
- A. Data compartmentalization.
- B. Differential privacy.
- C. Transfer learning.
- D. Clustering.
正解：B
解説：
Differential privacy is a technique used to ensure that the inclusion or exclusion of a single data point does not significantly affect the outcome of any analysis, providing a way to mathematically prove that no specific piece of training data has more than a negligible effect on the model or its output. This is achieved by introducing randomness into the data or the algorithms processing the data. In the context of training large language models (LLMs), differential privacy helps in protecting individual data points while still enabling the model to learn effectively. By adding noise to the training process, differential privacy provides strong guarantees about the privacy of the training data.
Reference: AIGP BODY OF KNOWLEDGE, pages related to data privacy and security in model training.
質問 # 52
What is the primary purpose of an Al impact assessment?
- A. Anticipate and manage the potential risks and harms of an Al system.
- B. To define and evaluate the legal risks associated with developing an Al system.
- C. To identify and measure the benefits of an Al system.
- D. To define and document the roles and responsibilities of Al stakeholders.
正解：A
解説：
The primary purpose of an AI impact assessment is to anticipate and manage the potential risks and harms of an AI system. This includes identifying the possible negative outcomes and implementing measures to mitigate these risks. This process helps ensure that AI systems are developed and deployed in a manner that is ethically and socially responsible, addressing concerns such as bias, fairness, transparency, and accountability.
The assessment often involves a thorough evaluation of the AI system's design, data inputs, outputs, and the potential impact on various stakeholders. This approach is crucial for maintaining public trust and adherence to regulatory requirements.
質問 # 53
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.
During the procurement process, what is the most likely reason that the third-party consultant asked each vendor for information about the diversity of their datasets?
- A. To determine the explainability of the Al system.
- B. To evaluate the reliability of the Al system.
- C. To assist the fairness of the Al system.
- D. To comply with applicable law.
正解：C
解説：
The third-party consultant asked each vendor for information about the diversity of their datasets to assist in ensuring the fairness of the AI system. Diverse datasets help prevent biases and ensure that the AI system performs equitably across different demographic groups. This is crucial for a law enforcement application, where fairness and avoiding discriminatory practices are of paramount importance. Ensuring diversity in training data helps in building a more just and unbiased AI system. Reference: AIGP Body of Knowledge on Ethical AI and Fairness.
質問 # 54
CASE STUDY
Please use the following answer the next question:
XYZ Corp., a premier payroll services company that employs thousands of people globally, is embarking on a new hiring campaign and wants to implement policies and procedures to identify and retain the best talent.
The new talent will help the company's product team expand its payroll offerings to companies in the healthcare and transportation sectors, including in Asia.
It has become time consuming and expensive for HR to review all resumes, and they are concerned that human reviewers might be susceptible to bias.
Address these concerns, the company is considering using a third-party Al tool to screen resumes and assist with hiring. They have been talking to several vendors about possibly obtaining a third-party Al-enabled hiring solution, as long as it would achieve its goals and comply with all applicable laws.
The organization has a large procurement team that is responsible for the contracting of technology solutions.
One of the procurement team's goals is to reduce costs, and it often prefers lower-cost solutions. Others within the company are responsible for integrating and deploying technology solutions into the organization's operations in a responsible, cost-effective manner.
The organization is aware of the risks presented by Al hiring tools and wants to mitigate them. It also questions how best to organize and train its existing personnel to use the Al hiring tool responsibly. Their concerns are heightened by the fact that relevant laws vary across jurisdictions and continue to change.
If XYZ does not deploy and use the Al hiring tool responsibly in the United States, its liability would likely increase under all of the following laws EXCEPT?
- A. Accessibility laws.
- B. Product liability laws.
- C. Privacy laws.
- D. Anti-discriminationlaws.
正解：B
解説：
In the United States, the use of AI hiring tools must comply with anti-discrimination laws, accessibility laws, and privacy laws to avoid increasing liability. Anti-discrimination laws (A) ensure that hiring practices do not unlawfully discriminate against protected classes. Accessibility laws (C) require that hiring tools are accessible to all applicants, including those with disabilities. Privacy laws (D) govern the handling of personal data during the hiring process. Product liability laws (B), however, typically apply to the safety and reliability of physical products and would not generally increase liability specifically related to the responsible use of AI hiring tools in the employment context.
質問 # 55
CASE STUDY
A company is considering the procurement of an AI system designed to enhance the security of IT infrastructure. The AI system analyzes how users type on their laptops, including typing speed, rhythm and pressure, to create a unique user profile. This data is then used to authenticate users and ensure that only authorized personnel can access sensitive resources.
The data processed by the AI system would be classified as:
- A. Non-personal data, as long as it is not linked to a user ID
- B. Special category data, if it can be used to uniquely identify a person
- C. Non-sensitive personal data, since it does not reveal information about health, gender or race
- D. Organizational data, since it is part of the authentication process
正解：B
解説：
The correct answer is D. Keystroke dynamics, used to identify individuals, fall under biometric data, which is a special category of personal data under the GDPR and other frameworks.
From the AI Governance in Practice Report 2024:
"Keystroke dynamics may constitute biometric data if used to uniquely identify an individual... Biometric data is classified as special category personal data and requires higher protection standards." Also reflected in ILT Participant Guide:
"Biometric data, such as facial images, voiceprints, iris scans or keystroke patterns, are treated as special category data when they are used for the purpose of uniquely identifying individuals."
質問 # 56
All of the following may be permissible uses of an Al system under the EU Al Act EXCEPT?
- A. To manage border control.
- B. To promote equitable distribution of welfare benefits.
- C. To implement social scoring.
- D. To detect an individual's intent for law enforcement purposes.
正解：C
解説：
The EU AI Act explicitly prohibits the use of AI systems for social scoring by public authorities, as it can lead to discrimination and unfair treatment of individuals based on their social behavior or perceived trustworthiness. While AI can be used to promote equitable distribution of welfare benefits, manage border control, and even detect an individual's intent for law enforcement purposes (within strict regulatory and ethical boundaries), implementing social scoring systems is not permissible under the Act due to the significant risks to fundamental rights and freedoms.
質問 # 57
Scenario:
A financial services company is planning a new AI project to assess creditworthiness. The AI team is mapping out what tasks should be completed during the planning phase of the AI lifecycle.
The planning phase of the AI lifecycle includes all of the following EXCEPT:
- A. Definition of underlying assumptions
- B. Context in which the model will operate
- C. Choice of the architecture
- D. Approach to governance
正解：C
解説：
The correct answer is C. The choice of architecture (e.g., neural networks vs. decision trees) is typically part of the design and development phase, not the initial planning.
From the AIGP Body of Knowledge - AI Lifecycle Module:
"Planning involves scoping, context definition, stakeholder identification, governance planning, and assumptions-not yet model selection." Confirmed in the ILT Participant Guide:
"Design decisions such as architecture or algorithm type come after planning-usually during development based on technical feasibility and data availability."
質問 # 58
CASE STUDY
Please use the following answer the next question:
XYZ Corp., a premier payroll services company that employs thousands of people globally, is embarking on a new hiring campaign and wants to implement policies and procedures to identify and retain the best talent. The new talent will help the company's product team expand its payroll offerings to companies in the healthcare and transportation sectors, including in Asia.
It has become time consuming and expensive for HR to review all resumes, and they are concerned that human reviewers might be susceptible to bias.
Address these concerns, the company is considering using a third-party Al tool to screen resumes and assist with hiring. They have been talking to several vendors about possibly obtaining a third-party Al-enabled hiring solution, as long as it would achieve its goals and comply with all applicable laws.
The organization has a large procurement team that is responsible for the contracting of technology solutions.
One of the procurement team's goals is to reduce costs, and it often prefers lower-cost solutions. Others within the company are responsible for integrating and deploying technology solutions into the organization's operations in a responsible, cost-effective manner.
The organization is aware of the risks presented by Al hiring tools and wants to mitigate them. It also questions how best to organize and train its existing personnel to use the Al hiring tool responsibly. Their concerns are heightened by the fact that relevant laws vary across jurisdictions and continue to change.
Which of the following measures should XYZ adopt to best mitigate its risk of reputational harm from using the Al tool?
- A. Continue to require XYZ's hiring personnel to manually screen all applicants.
- B. Test the Al tool pre- and post-deployment.
- C. Direct the procurement team to select the most economical Al tool.
- D. Ensure the vendor assumes responsibility for all damages.
正解：B
解説：
To mitigate the risk of reputational harm from using an AI hiring tool, XYZ Corp should rigorously test the AI tool both before and after deployment. Pre-deployment testing ensures the tool works correctly and does not introduce bias or other issues. Post-deployment testing ensures the tool continues to operate as intended and adapts to any changes in data or usage patterns. This approach helps to identify and address potential issues proactively, thereby reducing the risk of reputational harm. Ensuring the vendor assumes responsibility for damages (B) does not address the root cause of potential issues, selecting the most economical tool (C) may compromise quality, and continuing manual screening (D) defeats the purpose of using the AI tool.
質問 # 59
Scenario:
An organization is developing a powerful general-purpose AI (GPAI) model that has systemic impact. The compliance team is assessing what legal obligations apply under the EU AI Act.
Under the EU AI Act, which of the following compliance actions applies only to General Purpose AI models with systemic risk?
- A. Publishing a detailed summary of the data used to train the model
- B. Making information available to downstream providers who integrate the model into their AI systems
- C. Maintaining up-to-date technical documentation, including testing details
- D. Implementing an intellectual property policy to comply with EU copyright laws
正解：A
解説：
The correct answer is A. Only GPAI models with systemic risk must publish a detailed summary of training data to meet transparency and accountability standards under the EU AI Act.
From the AI Governance in Practice Report 2024 (EU AI Act Section):
"For GPAI systems with systemic risk, providers must publish sufficiently detailed summaries of the content used to train the model." Also, the AIGP ILT Guide confirms:
"The obligation to disclose summaries of training data applies only to systemic-risk GPAI models, not all general-purpose models or high-risk systems." This unique requirement is part of the Act's effort to increase transparency and auditability for powerful foundational models.
質問 # 60
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?
- A. Developing documentation on the system, the potential risks and the safeguards applied.
- B. Developing a reporting plan for any observed algorithmic discrimination or harms to individuals' rights and freedoms.
- C. Implementing a risk management framework.
- D. Conducting an impact assessment including a post-deployment monitoring plan.
正解：A
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 Report 2024:
"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 # 61
CASE STUDY
Please use the following answer the next question:
XYZ Corp., a premier payroll services company that employs thousands of people globally, is embarking on a new hiring campaign and wants to implement policies and procedures to identify and retain the best talent.
The new talent will help the company's product team expand its payroll offerings to companies in the healthcare and transportation sectors, including in Asia.
It has become time consuming and expensive for HR to review all resumes, and they are concerned that human reviewers might be susceptible to bias.
Address these concerns, the company is considering using a third-party Al tool to screen resumes and assist with hiring. They have been talking to several vendors about possibly obtaining a third-party Al-enabled hiring solution, as long as it would achieve its goals and comply with all applicable laws.
The organization has a large procurement team that is responsible for the contracting of technology solutions.
One of the procurement team's goals is to reduce costs, and it often prefers lower-cost solutions. Others within the company are responsible for integrating and deploying technology solutions into the organization's operations in a responsible, cost-effective manner.
The organization is aware of the risks presented by Al hiring tools and wants to mitigate them. It also questions how best to organize and train its existing personnel to use the Al hiring tool responsibly. Their concerns are heightened by the fact that relevant laws vary across jurisdictions and continue to change.
The frameworks that would be most appropriate for XYZ's governance needs would be the NIST Al Risk Management Framework and?
- A. IEEE Ethical System Design Risk Management Framework (IEEE 7000-21).
- B. Human Rights, Democracy, and Rule of Law Impact Assessment (HUDERIA).
- C. NIST Cyber Security Risk Management Framework (CSF 2.0).
- D. NIST Information Security Risk (NIST SP 800-39).
正解：A
解説：
The IEEE Ethical System Design Risk Management Framework (IEEE 7000-21) would be most appropriate for XYZ Corp's governance needs in addition to the NIST AI Risk Management Framework. The IEEE framework specifically addresses ethical concerns during system design, which is crucial for ensuring the responsible use of AI in hiring. It complements the NIST framework by focusing on ethical risk management, aligning well with XYZ Corp's goals of deploying AI responsibly and mitigating associated risks.
質問 # 62
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