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IAPP AIGP Exam Syllabus Topics:

Topic	Details
Topic 1	Understanding the Foundations of AI Governance: This section of the exam measures skills of AI governance professionals and covers the core concepts of AI governance, including what AI is, why governance is needed, and the risks and unique characteristics associated with AI. It also addresses the establishment and communication of organizational expectations for AI governance, such as defining roles, fostering cross-functional collaboration, and delivering training on AI strategies. Additionally, it focuses on developing policies and procedures that ensure oversight and accountability throughout the AI lifecycle, including managing third-party risks and updating privacy and security practices.
Topic 2	Understanding How Laws, Standards, and Frameworks Apply to AI: This section of the exam measures skills of compliance officers and covers the application of existing and emerging legal requirements to AI systems. It explores how data privacy laws, intellectual property, non-discrimination, consumer protection, and product liability laws impact AI. The domain also examines the main elements of the EU AI Act, such as risk classification and requirements for different AI risk levels, as well as enforcement mechanisms. Furthermore, it addresses the key industry standards and frameworks, including OECD principles, NIST AI Risk Management Framework, and ISO AI standards, guiding organizations in trustworthy and compliant AI implementation.
Topic 3	Understanding How to Govern AI Development: This section of the exam measures the skills of AI project managers and covers the governance responsibilities involved in designing, building, training, testing, and maintaining AI models. It emphasizes defining the business context, performing impact assessments, applying relevant laws and best practices, and managing risks during model development. The domain also includes establishing data governance for training and testing, ensuring data quality and provenance, and documenting processes for compliance. Additionally, it focuses on preparing models for release, continuous monitoring, maintenance, incident management, and transparent disclosures to stakeholders.
Topic 4	Understanding How to Govern AI Deployment and Use: This section of the exam measures skills of technology deployment leads and covers the responsibilities associated with selecting, deploying, and using AI models in a responsible manner. It includes evaluating key factors and risks before deployment, understanding different model types and deployment options, and ensuring ongoing monitoring and maintenance. The domain applies to both proprietary and third-party AI models, emphasizing the importance of transparency, ethical considerations, and continuous oversight throughout the model’s operational life.

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q109-Q114):

NEW QUESTION # 109
A US hospital plans to develop an AI that will review available patient data in order to propose an initial diagnosis to licensed physicians. The hospital will implement a policy that requires physicians to consider the AI proposal, but conduct their own physical examinations prior to making a final diagnosis. An important ethical concern with this plan is:

A. Whether physicians understand how the AI works.
B. Whether patients will receive an economic benefit from the use of AI.
C. Whether the AI will have an error rate comparable to human physicians.
D. Whether the AI was trained on a representative dataset.

Answer: D

Explanation:
Ensuring the AI is trained on representative data is crucial to avoid biased or inaccurate diagnostic proposals that could negatively impact patient care.

NEW QUESTION # 110
What is the primary reason the EU is considering updates to its Product Liability Directive?

A. To define new liability exemptions for defective products.
B. To address digital services and connected products.
C. To increase the minimum warranty level for defective goods.
D. To address free and open-source software.

Answer: B

Explanation:
The EU's update to the Product Liability Directive primarily aims to address the challenges posed by digital services and connected products, ensuring that liability rules are fit for purpose in the digital age and the circular economy.

NEW QUESTION # 111
MULTI-SELECT
Please select 3 of the 5 options below. No partial credit will be given.
From a governance perspective, which of the following correctly describe the responsibilities of AI developers or deployers?

A. AI deployers must handle ongoing monitoring and auditing of the AI system.
B. AI developers remain fully liable for the AI system ' s compliance with regulations even after deployment by others.
C. AI deployers must conduct independent bias assessments prior to release of a system.
D. AI developers are responsible for reducing biases in the system, such as discrimination against certain demographics.
E. AI developers must provide clear documentation explaining how the system functions for its operators.

Answer: A,D,E

Explanation:
The correct answers are A, C, and E because they reflect the shared but distinct responsibilities between AI developers and deployers in governance frameworks. Developers are responsible for designing systems that minimize bias and ensuring fairness during development. They are also required to provide clear documentation, including instructions for use, system capabilities, and limitations, to support transparency and proper operation. Deployers, on the other hand, are responsible for overseeing the system once it is in use, including continuous monitoring, auditing, and ensuring it performs as intended in real-world conditions.
Option B is incorrect because liability is typically shared and depends on roles and context, not solely on developers. Option D is incorrect because independent bias assessments are not always strictly required of deployers before release.

NEW QUESTION # 112
What is the key feature of Graphical Processing Units (GPUs) that makes them well-suited to running Al applications?

A. GPUs can run every task on a computer, making them more robust than CPUs.
B. The number of transistors on GPUs doubles every two years, making thechips smaller and lighter.
C. GPUs run many tasks concurrently, resulting in faster processing.
D. GPUs can access memory quickly, resulting in lower latency than CPUs.

Answer: C

Explanation:
GPUs (Graphical Processing Units) are well-suited to running AI applications due to their ability to run many tasks concurrently, which significantly enhances processing speed. This parallel processing capability makes GPUs ideal for handling the large-scale computations required in AI and deep learning tasks. Reference:
AIGP BODY OF KNOWLEDGE, which explains the importance of compute infrastructure in AI applications.

NEW QUESTION # 113
An organization establishes a cross-functional AI governance committee including legal, engineering, compliance, and HR teams. What is the primary purpose of this approach?

A. To accelerate AI deployment timelines
B. To centralize technical decision-making
C. To ensure diverse expertise and risk perspectives
D. To reduce the need for external audits

Answer: C

NEW QUESTION # 114
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