AIGP study materials: IAPP Certified Artificial Intelligence Governance Professional & AIGP exam torrent & AIGP actual exam

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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 (Q128-Q133):

NEW QUESTION # 128
Retrieval-Augmented Generation (RAG) is defined as:

A. Fine tuning LLMs to minimize biased outputs.
B. Reducing computational processing requirements of the LLMs.
C. Applying advanced filtering techniques to the LLMs.
D. Combining LLMs with private knowledge bases to improve their outputs.

Answer: D

Explanation:
RAG integrates large language models with external or private knowledge bases so the model can retrieve relevant information and generate more accurate, context-aware outputs.

NEW QUESTION # 129
A company that deploys AI but is not currently a provider or developer intends to develop and market its own AI system. Which obligation would then be likely to apply?

A. Implementing a risk management framework.
B. Conducting an impact assessment including a post-deployment monitoring plan.
C. Developing documentation on the system, the potential risks and the safeguards applied.
D. Developing a reporting plan for any observed algorithmic discrimination or harms to individuals' rights and freedoms.

Answer: A

Explanation:
Once the company becomes a provider of an AI system, it becomes subject to the EU AI Act's provider obligations, the foundational one being the requirement to implement a formal risk- management framework for the system throughout its lifecycle.

NEW QUESTION # 130
All of the following may be copyright risks from teachers using generative AI to create course content EXCEPT?

A. Generative AI is generally trained using intellectual property owned by third parties.
B. Students must expressly consent to this use of generative AI.
C. Generative AI often creates content without attribution.
D. Content created by an LLM may be protectable under U.S. intellectual property law.

Answer: B

NEW QUESTION # 131
Cloud-based deployment of AI often has which of the following advantages?

A. Increasing transparency.
B. Reducing latency at model inferencing.
C. Simplifying scaling up and down.
D. Enhancing privacy.

Answer: C

Explanation:
Cloud-based AI deployment simplifies scaling resources up or down on demand, providing flexibility and efficiency.

NEW QUESTION # 132
What is the primary objective of continuous monitoring in the lifecycle of an AI tool?

A. To periodically upgrade the AI tool's computational resources to maintain processing efficiency.
B. To ensure that the AI tool's algorithm evolves independently to adapt to new data without human intervention.
C. To track and adjust the tool's performance in order to ensure that it meets its goals.
D. To restrict the AI tool from accessing external data sources to maintain data privacy.

Answer: C

Explanation:
Continuous monitoring aims to track and adjust the AI tool's performance over time to ensure it consistently meets intended goals and operates effectively.

NEW QUESTION # 133
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