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NEW QUESTION # 48
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. Supply Chain and Marketing.
- B. Marketing and Compliance.
- C. Finance and Legal.
- D. Litigation and Product Development.
Answer: C
Explanation:
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.
NEW QUESTION # 49
Which of the following is the least relevant consideration in assessing whether users should be given the right to opt out from an Al system?
- A. Feasibility.
- B. Industry practice.
- C. Risk to users.
- D. Cost of alternative mechanisms.
Answer: D
Explanation:
When assessing whether users should be given the right to opt out from an AI system, the primary considerations are feasibility, risk to users, and industry practice. Feasibility addresses whether the opt-out mechanism can be practically implemented. Risk to users assesses the potential harm or benefits users might face if they cannot opt out. Industry practice considers the norms and standards within the industry. However, the cost of alternative mechanisms, while important in the broader context of implementation, is not directly relevant to the ethical consideration of whether users should have the right to opt out. The focus should be on protecting user rights and ensuring ethical AI practices.
Reference: AIGP BODY OF KNOWLEDGE, sections discussing user rights and ethical considerations in AI.
NEW QUESTION # 50
Which of the following would be the least likely step for an organization to take when designing an integrated compliance strategy for responsible Al?
- A. Conducting an assessment of existing compliance programs to determine overlaps and integration points.
- B. Launching a survey to understand the concerns and interests of potentially impacted stakeholders.
- C. Employing a new software platform to modernize existing compliance processes across the organization.
- D. Consulting experts to consider the ethical principles underpinning the use of Al within the organization.
Answer: C
Explanation:
When designing an integrated compliance strategy for responsible AI, the least likely step would be employing a new software platform to modernize existing compliance processes. While modernizing compliance processes is beneficial, it is not as directly related to the strategic integration of ethical principles and stakeholder concerns. More critical steps include conducting assessments of existing compliance programs to identify overlaps and integration points, consulting experts on ethical principles, and launching surveys to understand stakeholder concerns. These steps ensure that the compliance strategy is comprehensive and aligned with responsible AI principles. Reference: AIGP Body of Knowledge on AI Governance and Compliance Integration.
NEW QUESTION # 51
What is the 1956 Dartmouth summer research project on Al best known as?
- A. A meeting focused on the impacts of the launch of the first mass-produced computer.
- B. A meeting focused on the founding of the Al field.
- C. A research project to create a test for machine intelligence.
- D. A research project on the impacts of technology on society.
Answer: B
Explanation:
The 1956 Dartmouth summer research project on AI is best known as a meeting focused on the founding of the AI field. This conference is historically significant because it marked the formal beginning of artificial intelligence as an academic discipline. The term "artificial intelligence" was coined during this event, and it laid the foundation for future research and development in AI.
Reference: The AIGP Body of Knowledge highlights the importance of the Dartmouth Conference as a pivotal moment in the history of AI, which established AI as a distinct field of study and research.
NEW QUESTION # 52
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. Anti-discriminationlaws.
- B. Accessibility laws.
- C. Product liability laws.
- D. Privacy laws.
Answer: C
Explanation:
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.
NEW QUESTION # 53
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.
All of the following are potential negative consequences created by using the Al tool when making hiring decisions EXCEPT?
- A. Civil rights violations.
- B. Discriminatory treatment.
- C. Reputational harm.
- D. Intellectual property infringement.
Answer: D
Explanation:
The potential negative consequences of using an AI tool in hiring include reputational harm (A), civil rights violations (B), and discriminatory treatment (C). These issues stem from biases in the AI system or its misuse, which can lead to unfair hiring practices and legal liabilities. Intellectual property infringement (D) is not a typical consequence of using AI in hiring, as it relates to the unauthorized use of protected intellectual property, which is not directly relevant to the hiring process or the potential biases within AI tools.
NEW QUESTION # 54
Under the NIST Al Risk Management Framework, all of the following are defined as characteristics of trustworthy Al EXCEPT?
- A. Secure and Resilient.
- B. Accountable and Transparent.
- C. Tested and Effective.
- D. Explainable and Interpretable.
Answer: C
Explanation:
The NIST AI Risk Management Framework outlines several characteristics of trustworthy AI, including being secure and resilient, explainable and interpretable, and accountable and transparent. While being tested and effective is important, it is not explicitly listed as a characteristic of trustworthy AI in the NIST framework.
The focus is more on the system's ability to function safely, securely, and transparently in a way that stakeholders can understand and trust. Reference: AIGP Body of Knowledge, NIST AI RMF section.
NEW QUESTION # 55
According to the GDPR, what is an effective control to prevent a determination based solely on automated decision-making?
- A. Define suitable measures to safeguard personal data.
- B. Provide a right to review automated decision.
- C. Provide a just-in-time notice about the automated decision-making logic.
- D. Establish a human-in-the-loop procedure.
Answer: D
Explanation:
The GDPR requires that individuals have the right to not be subject to decisions based solely on automated processing, including profiling, unless specific exceptions apply. One effective control is to establish a human-in-the-loop procedure (D), ensuring human oversight and the ability to contest decisions. This goes beyond just-in-time notices (A), data safeguarding (B), or review rights (C), providing a more robust mechanism to protect individuals' rights.
NEW QUESTION # 56
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. Feature drift.
- C. System cost.
- D. Model drift.
Answer: C
Explanation:
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.
NEW QUESTION # 57
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.
In the design phase, what is the most important step for the healthcare network to take when mapping its existing data to the clinical research partner data?
- A. Identify fits and gaps in the combined data.
- B. Evaluate the country of origin of the data.
- C. Apply privacy-enhancing technologies to the data.
- D. Ensure the data is labeled and formatted.
Answer: A
Explanation:
In the design phase of integrating data from different sources, identifying fits and gaps is crucial. This process involves understanding how well the data from the clinical research partner aligns with the healthcare network's existing data. It ensures that the combined data set is coherent and can be effectively used for training the AI algorithm. This step helps in spotting any discrepancies, inconsistencies, or missing data that might affect the performance and accuracy of the AI model. It directly addresses the integrity and compatibility of the data, which is foundational before applying any privacy-enhancing technologies, labeling, or evaluating the origin of the data. Reference: AIGP Body of Knowledge on Data Integration and Quality.
NEW QUESTION # 58
Which of the following best defines an "Al model"?
- A. A system that applies defined rules to execute tasks.
- B. A program that has been trained on a set of data to find patterns within the data.
- C. A system of controls that is used to govern an Al algorithm.
- D. A corpus of data which an Al algorithm analyzes to make predictions.
Answer: B
Explanation:
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.
NEW QUESTION # 59
Scenario:
An enterprise is evaluating multiple third-party generative AI tools to integrate into its platform. As part of its AI governance policy, it is assessing the most effective methods to reduce risks related to bias, data misuse, and liability when using third-party solutions.
All of the following are commonly adopted processes and policies in reducing potential risks introduced by third-party AI tools or applications EXCEPT:
- A. Requiring new use cases of the generative AI tools or applications to be reviewed and approved by the generative AI governance body
- B. Including clauses in the procurement agreement for buyers of generative AI tools to put certain liabilities on the tool supplier
- C. Allowing publicly available information and personally identifiable information (PII) to be incorporated into the prompt
- D. Requiring an independent third-party bias audit for third-party generative AI tools
Answer: C
Explanation:
The correct answer is B. Allowing PII to be freely entered into prompts without safeguards is considered a major privacy and security risk and is not a responsible governance practice.
From the AIGP ILT Guide - Generative AI & Third-Party Risk Management:
"Use of personal or sensitive information in AI prompts can result in unintended exposure, regulatory breaches, and downstream liability." The AI Governance in Practice Report 2024 highlights:
"PII should be minimized or protected by design. Prompt engineering should prevent entry of personally identifiable data unless legally and technically safeguarded." A, C, and D are established best practices under responsible AI procurement and use.
NEW QUESTION # 60
The framework set forth in the White House Blueprint for an Al Bill of Rights addresses all of the following EXCEPT?
- A. Human alternatives, consideration and fallback.
- B. High-risk mitigation standards.
- C. Safe and effective systems.
- D. Data privacy.
Answer: B
Explanation:
The White House Blueprint for an AI Bill of Rights focuses on protecting civil rights, privacy, and ensuring AI systems are safe and effective. It includes principles like data privacy (D), human alternatives (A), and safe and effective systems (C). However, it does not specifically address high-risk mitigation standards as a distinct category (B).
NEW QUESTION # 61
An Al system that maintains its level of performance within defined acceptable limits despite real world or adversarial conditions would be described as?
- A. Resilient.
- B. Reinforced.
- C. Reliable.
- D. Robust.
Answer: A
Explanation:
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.
NEW QUESTION # 62
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.
In the design phase, which of the following steps is most important in gathering the data from the clinical research partner?
- A. Combine only anonymized data.
- B. Segregate the data sets.
- C. Review the terms of use.
- D. Perform a privacy impact assessment.
Answer: C
Explanation:
Reviewing the terms of use is essential when gathering data from a clinical research partner. This step ensures that the healthcare network complies with all legal and contractual obligations related to data usage. It addresses data ownership, usage limitations, consent requirements, and privacy obligations, which are critical to maintaining ethical standards and avoiding legal repercussions. This review helps ensure that the data is used in a manner consistent with the agreements made and the regulatory environment, which is fundamental for lawful and ethical AI development. Reference: AIGP Body of Knowledge on Legal and Regulatory Considerations.
NEW QUESTION # 63
Scenario:
A European AI technology company was found to be non-compliant with certain provisions of the EU AI Act.
The regulator is considering penalties under the enforcement provisions of the regulation.
According to the EU AI Act, which of the following non-compliance examples could lead to fines of up to €
15 million or 3% of annual worldwide turnover (whichever is higher)?
- A. In case of the supply of misleading information to notified bodies in reply to a request
- B. In case of AI Act prohibitions
- C. In case of a breach of AI Act prohibition by the Union institutions, bodies, offices and agencies
- D. In case of breach of a provider's obligations for high-risk AI systems
Answer: D
Explanation:
The correct answer is B. The EU AI Act assigns a tiered penalty system based on the severity of the violation. A breach of obligations related to high-risk AI systems falls into the mid-tier category, triggering fines of €15 million or 3% of annual global turnover.
From the AIGP ILT Guide - EU AI Act Module:
"Providers of high-risk AI systems must comply with strict documentation, testing, monitoring, and registration obligations. Breaches of these result in significant fines of up to €15 million or 3% of turnover." AI Governance in Practice Report 2024 supports this:
"Non-compliance with obligations under Title III (high-risk systems) leads to financial penalties under Article
71(3) of the EU AI Act."
Note: The highest penalty (€35 million or 7%) applies to prohibited AI uses, not to obligations for high- risk systems.
NEW QUESTION # 64
Scenario:
A large multinational organization is rolling out a company-wide AI governance initiative. To build awareness and support adoption, they are evaluating different ways to train employees and stakeholders across departments, including legal, technical, marketing, and customer-facing roles.
Which of the following typical approaches is a large organization least likely to use to responsibly train stakeholders on AI terminology, strategy and governance?
- A. Providing role-specific training, based on whether the organization uses a centralized, federated or decentralized governance model
- B. Providing information and education to customers and users to understand the capabilities and limitations of the AI tools with which they interact
- C. Providing all technical employees education on AI development so they can retool and participate in the development of AI systems
- D. Providing training on AI ethics, based on the extent to which the organization seeks to promote a responsible AI culture
Answer: C
Explanation:
The correct answer is A. While educating technical staff is important, expecting all technical employees to be retooled as AI developers is unrealistic and not aligned with scalable governance practices.
From the AIGP ILT Guide:
"Training approaches should be role-specific and align with the individual's function and responsibilities...
Organizations typically do not expect every technical role to participate in model development." The AI Governance in Practice Report 2024 supports tailored approaches:
"Cross-functional training should be specific to the individual's role and exposure to AI risk... Role-based education supports scalability and comprehension." Thus, broad development training for all technical employees is the least practical and least likely approach.
NEW QUESTION # 65
You are the chief privacy officer of a medical research company that would like to collect and use sensitive data about cancer patients, such as their names, addresses, race and ethnic origin, medical histories, insurance claims, pharmaceutical prescriptions, eating and drinking habits and physical activity.
The company will use this sensitive data to build an Al algorithm that will spot common attributes that will help predict if seemingly healthy people are more likely to get cancer. However, the company is unable to obtain consent from enough patients to sufficiently collect the minimum data to train its model.
Which of the following solutions would most efficiently balance privacy concerns with the lack of available data during the testing phase?
- A. Deploy the current model and recalibrate it over time with more data.
- B. Refocus the algorithm to patients without cancer.
- C. Utilize synthetic data to offset the lack of patient data.
- D. Extend the model to multi-modal ingestion with text and images.
Answer: C
Explanation:
Utilizing synthetic data to offset the lack of patient data is an efficient solution that balances privacy concerns with the need for sufficient data to train the model. Synthetic data can be generated to simulate real patient data while avoiding the privacy issues associated with using actual patient data. This approach allows for the development and testing of the AI algorithm without compromising patient privacy, and it can be refined with real data as it becomes available. Reference: AIGP Body of Knowledge on Data Privacy and AI Model Training.
NEW QUESTION # 66
Which of the following may be permissible uses of an AI system under the EU AI Act EXCEPT?
- A. Detecting emotions in a workplace for employee morale
- B. Using biometrics in abduction cases
- C. Improving the response time for emergency services
- D. Detecting emotions in a telemedicine session
Answer: A
Explanation:
The correct answer is D. Emotion recognition in the workplace is flagged as unacceptable or highly restricted under the EU AI Act due to its intrusive nature and potential for misuse.
From the AIGP ILT Guide - EU AI Act Training Module:
"AI systems that monitor individuals' emotions in the workplace or educational settings are listed among prohibited or strictly limited practices under Article 5." AI Governance in Practice Report 2024 supports this interpretation:
"Emotion recognition systems, especially in sensitive contexts such as employment or education, raise significant concerns under EU fundamental rights law and are likely to be restricted." Other uses listed-such as emergency response or emotion detection in healthcare-may fall under lawful and beneficial uses, especially when justified by public interest.
NEW QUESTION # 67
Which of the following disclosures is NOT required for an EU organization that developed and deployed a high-risk Al system?
- A. How an individual may contest a decision.
- B. The fact that an Al system is being used.
- C. The human oversight measures employed.
- D. The location(s) where data is stored.
Answer: D
Explanation:
Under the EU AI Act, organizations that develop and deploy high-risk AI systems are required to provide several key disclosures to ensure transparency and accountability. These include the human oversight measures employed, how individuals can contest decisions made by the AI system, and informing individuals that an AI system is being used. However, there is no specific requirement to disclose the exact locations where data is stored. The focus of the Act is on the transparency of the AI system's operation and its impact on individuals, rather than on the technical details of data storage locations.
NEW QUESTION # 68
Each of the following actors are typically engaged in the Al development life cycle EXCEPT?
- A. Government regulators.
- B. Data architects.
- C. Socio-cultural and technical experts.
- D. Legal and privacy governance experts.
Answer: A
Explanation:
Typically, actors involved in the AI development life cycle include data architects (who design the data frameworks), socio-cultural and technical experts (who ensure the AI system is socio-culturally aware and technically sound), and legal and privacy governance experts (who handle the legal and privacy aspects).
Government regulators, while important, are not directly engaged in the development process but rather oversee and regulate the industry. Reference: AIGP BODY OF KNOWLEDGE and AI development frameworks.
NEW QUESTION # 69
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