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[General] New IAPP AIGP Test Testking | Dump AIGP Torrent

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【General】 New IAPP AIGP Test Testking | Dump AIGP Torrent

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IAPP AIGP Exam Syllabus Topics:
TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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.
Topic 4
  • 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.

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q116-Q121):NEW QUESTION # 116
What is the most significant risk of deploying an AI model that can create realistic images and videos?
  • A. Copyright infringement.
  • B. Downstream harms.
  • C. Output cannot be protected.
  • D. Security breaches.
Answer: B
Explanation:
The greatest risk from AI systems generatingrealistic synthetic mediaisdownstream harm, such asdeepfakes, misinformation, reputational damage, and erosion of trust.
From theAI Governance in Practice Report2025:
"With generative AI, downstream harms such as deception, reputational damage, misinformation, and manipulation can emerge even if original use was lawful." (p. 55-56)

NEW QUESTION # 117
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. Data privacy.
  • C. High-risk mitigation standards.
  • D. Safe and effective systems.
Answer: C
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 # 118
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 information and education to customers and users to understand the capabilities and limitations of the AI tools with which they interact.
  • B. Providing training on AI ethics, based on the extent to which the organization seeks to promote a responsible AI culture.
  • C. Providing all technical employees education on AI development so they can retool and participate in the development of AI systems.
  • D. Providing role-specific training, based on whether the organization uses a centralized, federated or decentralized governance mode.
Answer: C
Explanation:
Large organizations are less likely to train all technical employees extensively on AI development, as this is resource-intensive and not necessary for all roles; instead, they focus on targeted, role- specific training aligned with governance and ethical goals.

NEW QUESTION # 119
The most important policy to assess the operations of an AI model is to follow the:
  • A. Security policy of the model provider.
  • B. Code of conduct policy of the model provider.
  • C. Privacy policy of the model provider.
  • D. Acceptable use policy of the model provider.
Answer: D
Explanation:
The acceptable use policy defines how the model is permitted to be operated, including restrictions, prohibited behaviors, and required safeguards. It is the most important policy for assessing whether the AI model is being used appropriately and within operational boundaries.

NEW QUESTION # 120
What is the key feature of Graphical Processing Units (GPUs) that makes them well-suited to running Al applications?
  • A. The number of transistors on GPUs doubles every two years, making thechips smaller and lighter.
  • B. GPUs can run every task on a computer, making them more robust than CPUs.
  • C. GPUs can access memory quickly, resulting in lower latency than CPUs.
  • D. GPUs run many tasks concurrently, resulting in faster processing.
Answer: D
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 # 121
......
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