[2025年01月09日] 最新でリアルなAIGP試験問題集解答
あなたを簡単に合格させるAIGP試験問と正確なIAPP Certified Artificial Intelligence Governance ProfessionalのPDF問題
質問 # 32
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 # 33
Pursuant to the White House Executive Order of November 2023, who is responsible for creating guidelines to conduct red-teaming tests of Al systems?
- A. Office of Science and Technology Policy (OSTP).
- B. Department of Homeland Security (DHS).
- C. National Institute of Standards and Technology (NIST).
- D. National Science and Technology Council (NSTC).
正解：C
解説：
The White House Executive Order of November 2023 designates the National Institute of Standards and Technology (NIST) as the responsible body for creating guidelines to conduct red-teaming tests of AI systems.
NIST is tasked with developing and providing standards and frameworks to ensure the security, reliability, and ethical deployment of AI systems, including conducting rigorous red-teaming exercises to identify vulnerabilities and assess risks in AI systems.
Reference: AIGP BODY OF KNOWLEDGE, sections on AI governance and regulatory frameworks, and the White House Executive Order of November 2023.
質問 # 34
Under the Canadian Artificial Intelligence and Data Act, when must the Minister of Innovation, Science and Industry be notified about a high-impact Al system?
- A. Upon initial deployment of the system.
- B. When use of the system causes or is likely to cause material harm.
- C. When the algorithmic impact assessment has been completed.
- D. Upon release of a new version of the system.
正解：A
解説：
According to the Canadian Artificial Intelligence and Data Act, high-impact AI systems must notify the Minister of Innovation, Science and Industry upon initial deployment. This requirement ensures that the authorities are aware of the deployment of significant AI systems and can monitor their impacts and compliance with regulatory standards from the outset. This initial notification is crucial for maintaining oversight and ensuring the responsible use of AI technologies. Reference: AIGP Body of Knowledge, domain on AI laws and standards.
質問 # 35
Random forest algorithms are in what type of machine learning model?
- A. Generative.
- B. Natural language processing.
- C. Symbolic.
- D. Discriminative.
正解：D
解説：
Random forest algorithms are classified as discriminative models. Discriminative models are used to classify data by learning the boundaries between classes, which is the core functionality of random forest algorithms.
They are used for classification and regression tasks by aggregating the results of multiple decision trees to make accurate predictions.
Reference: The AIGP Body of Knowledge explains that discriminative models, including random forest algorithms, are designed to distinguish between different classes in the data, making them effective for various predictive modeling tasks.
質問 # 36
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. Privacy laws.
- B. Accessibility laws.
- C. Product liability laws.
- D. Anti-discriminationlaws.
正解：C
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 # 37
CASE STUDY
Please use the following answer the next question:
Good Values Corporation (GVC) is a U.S. educational services provider that employs teachers to create and deliver enrichment courses for high school students. GVC has learned that many of its teacher employees are using generative Al to create the enrichment courses, and that many of the students are using generative Al to complete their assignments.
In particular, GVC has learned that the teachers they employ used open source large language models ("LLM") to develop an online tool that customizes study questions for individual students. GVC has also discovered that an art teacher has expressly incorporated the use of generative Al into the curriculum to enable students to use prompts to create digital art.
GVC has started to investigate these practices and develop a process to monitor any use of generative Al, including by teachers and students, going forward.
Which of the following risks should be of the highest concern to individual teachers using generative Al to ensure students learn the course material?
- A. Copyright infringement.
- B. Technical complexity.
- C. Model accuracy.
- D. Financial cost.
正解：C
解説：
The highest concern for individual teachers using generative AI to ensure students learn the course material is model accuracy. Ensuring that the AI-generated content is accurate and relevant to the curriculum is crucial for effective learning. If the AI model produces inaccurate or irrelevant content, it can mislead students and hinder their understanding of the subject matter.
Reference: According to the AIGP Body of Knowledge, one of the core risks posed by AI systems is the accuracy of the data and models used. Ensuring the accuracy of AI-generated content is essential for maintaining the integrity of the educational material and achieving the desired learning outcomes.
質問 # 38
In the machine learning context, feature engineering is the process of?
- A. Converting raw data into clean data.
- B. Creating learning schema for a model apply.
- C. Extracting attributes and variables from raw data.
- D. Developing guidelines to train and test a model.
正解：C
解説：
In the machine learning context, feature engineering is the process of extracting attributes and variables from raw data to make it suitable for training an AI model. This step is crucial as it transforms raw data into meaningful features that can improve the model's accuracy and performance. Feature engineering involves selecting, modifying, and creating new features that help the model learn more effectively. Reference: AIGP Body of Knowledge on AI Model Development and Feature Engineering.
質問 # 39
Testing data is defined as a subset of data that is used to?
- A. Provide a robust evaluation of a final model.
- B. Evaluate a model's handling of randomized edge cases.
- C. Enable a model to discover and learn patterns.
- D. Assess a model's on-going performance in production.
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 # 40
Which of the following deployments of generative Al best respects intellectual property rights?
- A. The system provides attribution to creators of publicly available information.
- B. The system produces content that includes trademarks and copyrights.
- C. The system produces content that is modified to closely resemble copyrightedwork.
- D. The system categorizes and applies filters to content based on licensing terms.
正解：D
解説：
Respecting intellectual property rights means adhering to licensing terms and ensuring that generated content complies with these terms. A system that categorizes and applies filters based on licensing terms ensures that content is used legally and ethically, respecting the rights of content creators. While providing attribution is important, categorization and application of filters based on licensing terms are more directly tied to compliance with intellectual property laws. This principle is elaborated in the IAPP AIGP Body of Knowledge sections on intellectual property and compliance.
質問 # 41
The White House Executive Order from November 2023 requires companies that develop dual-use foundation models to provide reports to the federal government about all of the following EXCEPT?
- A. The physical and cybersecurity protection measures of their dual-use foundation models.
- B. Any environmental impact study for each dual-use foundation model.
- C. Any current training or development of dual-use foundation models.
- D. The results of red-team testing of each dual-use foundation model.
正解：B
解説：
The White House Executive Order from November 2023 requires companies developing dual-use foundation models to report on their current training or development activities, the results of red-team testing, and the physical and cybersecurity protection measures. However, it does not mandate reports on environmental impact studies for each dual-use foundation model. While environmental considerations are important, they are not specified in this context as a reporting requirement under this Executive Order.
Reference: AIGP BODY OF KNOWLEDGE, sections on compliance and reporting requirements, and the White House Executive Order of November 2023.
質問 # 42
All of the following are common optimization techniques in deep learning to determine weights that represent the strength of the connection between artificial neurons EXCEPT?
- A. Backpropagation, which starts from the last layer working backwards.
- B. Autoregression, which analyzes and makes predictions about time-series data.
- C. Gradient descent, which initially sets weights arbitrary values, and then at each step changes them.
- D. Momentum, which improves the convergence speed and stability of neural network training.
正解：B
解説：
Autoregression is not a common optimization technique in deep learning to determine weights for artificial neurons. Common techniques include gradient descent, momentum, and backpropagation. Autoregression is more commonly associated with time-series analysis and forecasting rather than neural network optimization.
Reference: AIGP BODY OF KNOWLEDGE, which discusses common optimization techniques used in deep learning.
質問 # 43
What is the main purpose of accountability structures under the Govern function of the NIST Al Risk Management Framework?
- A. To empower and train appropriate cross-functional teams.
- B. To determine responsibility for allocating budgetary resources.
- C. To establish diverse, equitable and inclusive processes.
- D. To enable and encourage participation by external stakeholders.
正解：A
解説：
The NIST AI Risk Management Framework's Govern function emphasizes the importance of establishing accountability structures that empower and train cross-functional teams. This is crucial because cross-functional teams bring diverse perspectives and expertise, which are essential for effective AI governance and risk management. Training these teams ensures that they are well-equipped to handle their responsibilities and can make informed decisions that align with the organization's AI principles and ethical standards. Reference: NIST AI Risk Management Framework documentation, Govern function section.
質問 # 44
An EU bank intends to launch a multi-modal Al platform for customer engagement and automated decision-making assist with the opening of bank accounts. The platform has been subject to thorough risk assessments and testing, where it proves to be effective in not discriminating against any individual on the basis of a protected class.
What additional obligations must the bank fulfill prior to deployment?
- A. The bank must disclose how the Al system works under the Ell Digital Services Act.
- B. The bank must subject the Al system an adequacy decision and publish its appropriate safeguards.
- C. The bank must obtain explicit consent from users under the privacy Directive.
- D. The bank must disclose the use of the Al system and implement suitable measures for users to contest automated decision-making.
正解：D
解説：
Under the EU regulations, particularly the GDPR, banks using AI for decision-making must inform users about the use of AI and provide mechanisms for users to contest decisions. This is part of ensuring transparency and accountability in automated processing. Explicit consent under the privacy directive (A) and disclosing under the Digital Services Act (B) are not specifically required in this context. An adequacy decision is related to data transfers outside the EU (C).
質問 # 45
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.
When notifying an accused perpetrator, what additional information should a police officer provide about the use of the Al system?
- A. Information about the composition of the training data of the system.
- B. Information about how the individual was identified by the Al system.
- C. Information about the accuracy of the Al system.
- D. Information about how the accused can oppose the charges.
正解：B
解説：
When notifying an accused perpetrator, the police officer should provide information about how the individual was identified by the AI system. This transparency is crucial for maintaining trust and ensuring that the accused understands the basis of the charges against them. Information about the accuracy, how to oppose the charges, and the composition of the training data, while potentially relevant, do not directly address the immediate need for the accused to understand the specific process that led to their identification. Reference:
AIGP Body of Knowledge on AI Transparency and Explainability.
質問 # 46
Which of the following best defines an "Al model"?
- A. A system of controls that is used to govern an Al algorithm.
- B. A system that applies defined rules to execute tasks.
- C. A corpus of data which an Al algorithm analyzes to make predictions.
- D. A program that has been trained on a set of data to find patterns within the data.
正解：D
解説：
An AI model is best defined as a program that has been trained on a set of data to find patterns within that data. This definition captures the essence of machine learning, where the model learns from the data to make predictions or decisions. Reference: AIGP BODY OF KNOWLEDGE, which provides a detailed explanation of AI models and their training processes.
質問 # 47
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 other stakeholder groups should be involved in the selection and implementation of the Al hiring tool?
- A. Marketing and Compliance.
- B. Finance and Legal.
- C. Litigation and Product Development.
- D. Supply Chain and Marketing.
正解：B
解説：
In the selection and implementation of the AI hiring tool, involving Finance and Legal is crucial. The Finance team is essential for assessing cost implications, budget considerations, and financial risks. The Legal team is necessary to ensure compliance with applicable laws and regulations, including those related to data privacy, employment, and anti-discrimination. Involving these stakeholders ensures a comprehensive evaluation of both the financial viability and legal compliance of the AI tool, mitigating potential risks and aligning with organizational objectives and regulatory requirements.
質問 # 48
What is the best reason for a company adopt a policy that prohibits the use of generative Al?
- A. Avoid needing to identify and hire qualified resources.
- B. Avoid accidental disclosure to its confidential and proprietary information.
- C. Avoid using technology that cannot be monetized.
- D. Avoid the time necessary to train employees on acceptable use.
正解：B
解説：
The primary concern for a company adopting a policy prohibiting the use of generative AI is the risk of accidental disclosure of confidential and proprietary information. Generative AI tools can inadvertently leak sensitive data during the creation process or through data sharing. This risk outweighs the other reasons listed, as protecting sensitive information is critical to maintaining the company's competitive edge and legal compliance. This rationale is discussed in the sections on risk management and data privacy in the IAPP AIGP Body of Knowledge.
質問 # 49
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. Model drift.
- C. System cost.
- D. Feature drift.
正解：C
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 # 50
......
AIGP認証試験問題集の解答を提供しています：https://drive.google.com/open?id=1GBd2vObMgTh6mKKsLnj6D35m_iO8XyYU
更新されたAIGP試験練習テスト問題：https://www.goshiken.com/IAPP/AIGP-mondaishu.html