[2025年04月19日] 最速準備で試験合格！AIGP問題の事前予備
AIGPのPDF問題集リアル2025最近更新された問題
IAPP AIGP 認定試験の出題範囲：
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質問 # 40
A U.S. mortgage company developed an Al platform that was trained using anonymized details from mortgage applications, including the applicant's education, employment and demographic information, as well as from subsequent payment or default information. The Al platform will be used automatically grant or deny new mortgage applications, depending on whether the platform views an applicant as presenting a likely risk of default.
Which of the following laws is NOT relevant to this use case?
- A. Title VII of the Civil Rights Act of 1964.
- B. Fair Housing Act.
- C. Equal Credit Opportunity Act.
- D. Fair Credit Reporting Act.
正解：A
解説：
The U.S. mortgage company's AI platform relates to housing and credit, making the Fair Housing Act (A), Fair Credit Reporting Act (B), and Equal Credit Opportunity Act (C) relevant. Title VII of the Civil Rights Act of 1964 deals with employment discrimination and is not directly relevant to the mortgage application context (D).
質問 # 41
All of the following are elements of establishing a global Al governance infrastructure EXCEPT?
- A. Publicly disclosing ethical principles.
- B. Understanding differences in norms across countries.
- C. Creating policies and procedures to manage third-partyrisk.
- D. Providing training to foster a culture that promotes ethical behavior.
正解：A
解説：
Establishing a global AI governance infrastructure involves several key elements, including providing training to foster a culture that promotes ethical behavior, creating policies and procedures to manage third-party risk, and understanding differences in norms across countries. While publicly disclosing ethical principles can enhance transparency and trust, it is not a core element necessary for the establishment of a governance infrastructure. The focus is more on internal processes and structures rather than public disclosure. Reference:
AIGP Body of Knowledge on AI Governance and Infrastructure.
質問 # 42
CASE STUDY
Please use the following answer the next question:
A mid-size US healthcare network has decided to develop an Al solution to detect a type of cancer that is most likely 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 a radiologist for secondary review pursuant Agreed-upon criteria (e.g., a confidence score below a threshold).
To date, the healthcare network has taken the following steps: defined its Al ethical principles: conducted discovery to identify the intended uses and success criteria for the system: established an Al governance committee; assembled a broad, crossfunctional team with clear roles and responsibilities; and 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 and a consulting firm to 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.
The most significant risk from combining the healthcare network's existing data with the clinical research partner data is?
- A. Privacy risk.
- B. Security risk.
- C. Operational risk.
- D. Reputational risk.
正解：A
解説：
The most significant risk from combining the healthcare network's existing data with the clinical research partner data is privacy risk. Combining data sets, especially in healthcare, often involves handling sensitive information that could lead to privacy breaches if not managed properly. De-identified data can still pose re-identification risks when combined with other data sets. Ensuring privacy involves implementing robust data protection measures, maintaining compliance with privacy regulations such as HIPAA, and conducting thorough privacy impact assessments. Reference: AIGP Body of Knowledge on Data Privacy and Security.
質問 # 43
All of the following are included within the scope of post-deployment Al maintenance EXCEPT?
- A. Evaluating the need for an audit under certain standards.
- B. Ensuring that all model components are subject a control framework.
- C. Defining thresholds to conduct new impact assessments.
- D. Dedicating experts to continually monitor the model output.
正解：C
解説：
Post-deployment AI maintenance typically includes ensuring that all model components are subject to a control framework, dedicating experts to continually monitor the model output, and evaluating the need for audits under certain standards. However, defining thresholds to conduct new impact assessments is usually part of the initial deployment and ongoing governance processes rather than a maintenance activity.
Maintenance focuses more on the operational aspects of the AI system rather than setting new thresholds for impact assessments.
Reference: AIGP BODY OF KNOWLEDGE, sections discussing AI lifecycle management and post-deployment activities.
質問 # 44
Retraining an LLM can be necessary for all of the following reasons EXCEPT?
- A. Account for new interpretations of the same data.
- B. To minimize degradation in prediction accuracy due tochanges in data.
- C. Adjust the model's hyper parameters specific use case.
- D. To ensure interpretability of the model's predictions.
正解：D
解説：
Retraining an LLM (Large Language Model) is primarily done to improve or maintain its performance as data changes over time, to fine-tune it for specific use cases, and to incorporate new data interpretations to enhance accuracy and relevance. However, ensuring interpretability of the model's predictions is not typically a reason for retraining. Interpretability relates to how easily the outputs of the model can be understood and explained, which is generally addressed through different techniques or methods rather than through the retraining process itself. References to this can be found in the IAPP AIGP Body of Knowledge discussing model retraining and interpretability as separate concepts.
質問 # 45
Which type of existing assessment could best be leveraged to create an Al impact assessment?
- A. A safety impact assessment.
- B. A privacy impact assessment.
- C. A security impact assessment.
- D. An environmental impact assessment.
正解：B
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 # 46
When monitoring the functional performance of a model that has been deployed into production, all of the following are concerns EXCEPT?
- A. Data loss.
- B. System cost.
- C. Model drift.
- D. Feature drift.
正解：B
解説：
When monitoring the functional performance of a model deployed into production, concerns typically include feature drift, model drift, and data loss. Feature drift refers to changes in the input features that can affect the model's predictions. Model drift is when the model's performance degrades over time due to changes in the data or environment. Data loss can impact the accuracy and reliability of the model. However, system cost, while important for budgeting and financial planning, is not a direct concern when monitoring the functional performance of a deployed model. Reference: AIGP Body of Knowledge on Model Monitoring and Maintenance.
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 that are high-risk.
- B. Al systems that are "strong" general intelligence.
- C. Al systems trained on sensitive personal data.
- D. Al systems that are harmful based on a legal risk-utility calculation.
正解：A
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
Machine learning is best described as a type of algorithm by which?
- A. Previously unknown properties are discovered in data and used to predict and make improvements in the data.
- B. Systems can mimic human intelligence with the goal of replacing humans.
- C. Systems can automatically improve from experience through predictive patterns.
- D. Statistical inferences are drawn from a sample with the goal of predicting human intelligence.
正解：C
解説：
Machine learning (ML) is a subset of artificial intelligence (AI) where systems use data to learn and improve over time without being explicitly programmed. Option B accurately describes machine learning by stating that systems can automatically improve from experience through predictive patterns. This aligns with the fundamental concept of ML where algorithms analyze data, recognize patterns, and make decisions with minimal human intervention. Reference: AIGP BODY OF KNOWLEDGE, which covers the basics of AI and machine learning concepts.
質問 # 49
A company plans on procuring a tool from an Al provider for its employees to use for certain business purposes.
Which contractual provision would best protect the company's intellectual property in the tool, including training and testing data?
- A. The provider willgive privacy notice to individuals before using their personal data to train or test the tool.
- B. The provider willwarrant that the tool will work as intended.
- C. The provider willdefend and indemnify the company against infringement claims.
- D. The provider willobtain and maintain insurance to cover potential claims.
正解：C
解説：
To protect the company's intellectual property, the most pertinent contractual provision is ensuring that the AI provider will defend and indemnify the company against infringement claims. This clause means the provider will take responsibility for any intellectual property disputes that arise, thereby safeguarding the company from potential legal and financial repercussions related to the use of the tool. Other options, while beneficial, do not directly address the protection of intellectual property. This concept is detailed in the contractual best practices section of the IAPP AIGP Body of Knowledge.
質問 # 50
A Canadian company is developing an Al solution to evaluate candidates in the course of job interviews.
Before offering the Al solution in the EU market, the company must take all of the following steps EXCEPT?
- A. Establish a risk and quality management system.
- B. Engage a third-party auditor to perform a bias audit.
- C. Register the Al solution in a public EU database.
- D. Draw up technical documentation and instructions for use.
正解：C
解説：
Before offering an AI solution in the EU market, a Canadian company must take several steps to comply with the EU AI Act. These steps include establishing a risk and quality management system (B), engaging a third-party auditor to perform a bias audit (C), and drawing up technical documentation and instructions for use (D). However, there is no requirement to register the AI solution in a public EU database (A). This registration step is not specified as part of the compliance requirements under the EU AI Act for such solutions.
質問 # 51
All of the following are penalties and enforcements outlined in the EU Al Act EXCEPT?
- A. Fines for SMEs and startups will be proportionally capped.
- B. Fines for violations of banned Al applications will be €35 million or 7% global annual turnover (whichever is higher).
- C. Rules on General Purpose Al will apply after 6 months as a specific provision.
- D. The Al Pact will act as a transitional bridge until the Regulations are fully enacted.
正解：D
解説：
The EU AI Act outlines specific penalties and enforcement mechanisms to ensure compliance with its regulations. Among these, fines for violations of banned AI applications can be as high as €35 million or 7% of the global annual turnover of the offending organization, whichever is higher. Proportional caps on fines are applied to SMEs and startups to ensure fairness. General Purpose AI rules are to apply after a 6-month period as a specific provision to ensure that stakeholders have adequate time to comply. However, there is no provision for an "AI Pact" acting as a transitional bridge until the regulations are fully enacted, making option C the correct answer.
質問 # 52
You are a privacy program manager at a large e-commerce company that uses an Al tool to deliver personalized product recommendations based on visitors' personal information that has been collected from the company website, the chatbot and public data the company has scraped from social media.
A user submits a data access request under an applicable U.S. state privacy law, specifically seeking a copy of their personal data, including information used to create their profile for product recommendations.
What is the most challenging aspect of managing this request?
- A. Some of the data subject's data is unstructured data and you cannot untangle it from the other data, including information about other individuals.
- B. The data subject's data is structured data that can be searched, compiled and reviewed only by an automated tool.
- C. Some of the visitor's data is synthetic data that the company does not have to provide to the data subject.
- D. The data subject is not entitled to receive a copy of their data because some of it was scraped from public sources.
正解：A
解説：
The most challenging aspect of managing a data access request in this scenario is dealing with unstructured data that cannot be easily disentangled from other data, including information about other individuals.
Unstructured data, such as free-text inputs or social media posts, often lacks a clear structure and may be intermingled with data from multiple individuals, making it difficult to isolate the specific data related to the requester. This complexity poses significant challenges in complying with data access requests under privacy laws. Reference: AIGP Body of Knowledge on Data Subject Rights and Data Management.
質問 # 53
Testing data is defined as a subset of data that is used to?
- A. Provide a robust evaluation of a final model.
- B. Assess a model's on-going performance in production.
- C. Enable a model to discover and learn patterns.
- D. Evaluate a model's handling of randomized edge cases.
正解：A
解説：
Testing data is a subset of data used to provide a robust evaluation of a final model. After training the model on training data, it is essential to test its performance on unseen data (testing data) to ensure it generalizes well to new, real-world scenarios. This step helps in assessing the model's accuracy, reliability, and ability to handle various data inputs. Reference: AIGP Body of Knowledge on Model Validation and Testing.
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.
Which of the following measures should XYZ adopt to best mitigate its risk of reputational harm from using the Al tool?
- A. Test the Al tool pre- and post-deployment.
- B. Direct the procurement team to select the most economical Al tool.
- C. Ensure the vendor assumes responsibility for all damages.
- D. Continue to require XYZ's hiring personnel to manually screen all applicants.
正解：A
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 # 55
An Al system that maintains its level of performance within defined acceptable limits despite real world or adversarial conditions would be described as?
- A. Reinforced.
- B. Resilient.
- C. Robust.
- D. Reliable.
正解：B
解説：
An AI system that maintains its level of performance within defined acceptable limits despite real-world or adversarial conditions is described as resilient. Resilience in AI refers to the system's ability to withstand and recover from unexpected challenges, such as cyber-attacks, hardware failures, or unusual input data. This characteristic ensures that the AI system can continue to function effectively and reliably in various conditions, maintaining performance and integrity. Robustness, on the other hand, focuses on the system's strength against errors, while reliability ensures consistent performance over time. Resilience combines these aspects with the capacity to adapt and recover.
質問 # 56
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