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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Foundational Concepts of AI Governance | 24–28% | - Principles of responsible, ethical and trustworthy AI - Governance frameworks and core concepts - Fundamental AI definitions, types and characteristics - Impacts, risks and benefits of AI systems |
| Topic 2: Governance of AI Development | 21–25% | - Governance through design and lifecycle management - Testing, validation, documentation and transparency - Model management, version control and quality assurance - Requirements gathering, risk assessment and mitigation |
| Topic 3: Laws, Regulations, Standards and Frameworks | 24–28% | - International standards (ISO 42001, NIST AI RMF, etc.) - Global and regional regulations (EU AI Act, US, etc.) - Sector-specific requirements and compliance obligations - Alignment with data protection and privacy laws |
| Topic 4: Governance of AI Deployment and Use | 21–25% | - Selection, procurement and third-party management - Implementation, monitoring and ongoing oversight - Lifecycle maintenance, decommissioning and updates - Incident response, accountability and audit |
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NEW QUESTION # 43
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?
Answer: D
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 # 44
CASE STUDY
Please use the following to answer the next question:
A mid-size US healthcare network has decided to develop an AI solution to detect a type of cancer that is most likely to 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 to a radiologist for secondary review pursuant to agreed-upon criteria (e.g., a confidence score below a threshold).
To date, the healthcare network has:
- Defined its AI ethical principles.
- Conducted discovery to identify the intended uses and success
criteria for the system.
- Established an AI risk committee.
- Assembled a cross-functional team with clear roles and
responsibilities.
- 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. It also intends to retain a large consulting firm to supplement its small data science team and 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?
Answer: D
Explanation:
Reviewing the terms of use is essential to ensure legal compliance and appropriate permissions when gathering data from the clinical research partner during the design phase.
NEW QUESTION # 45
According to the Singapore Model Al Governance Framework, all of the following are recommended measures to promote the responsible use of Al EXCEPT?
Answer: A
Explanation:
The Singapore Model AI Governance Framework recommends several measures to promote the responsible use of AI, such as determining the level of human involvement in decision-making, adapting governance structures, and establishing communications and collaboration among stakeholders. However, employing human-over-the-loop protocols is not specifically mentioned in this framework. The focus is more on integrating human oversight appropriately within the decision-making process rather than exclusively employing such protocols. Reference: AIGP Body of Knowledge, section on AI governance frameworks.
NEW QUESTION # 46
The initial pilot effort for NIST's Assessing Risks and Impacts of AI (ARIA) Program is focused on risks associated with which of the following?
Answer: D
Explanation:
The initial pilot effort of the NIST ARIA (Assessing Risks and Impacts of AI) Program focuses on evaluating risks and impacts associated with large language models (LLMs). This evaluation aims to assess how LLMs perform in real-world contexts, including their robustness, reliability, and potential societal impacts.
NEW QUESTION # 47
Training data is best defined as a subset of data that is used to?
Answer: B
Explanation:
Training data is used to enable a model to detect and learn patterns. During the training phase, the model learns from the labeled data, identifying patterns and relationships that it will later use to make predictions on new, unseen data. This process is fundamental in building an AI model's capability to perform tasks accurately. Reference: AIGP Body of Knowledge on Model Training and Pattern Recognition.
NEW QUESTION # 48
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