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[General] Latest Braindumps AIGP Book, Latest AIGP Study Notes

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【General】 Latest Braindumps AIGP Book, Latest AIGP Study Notes

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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.

IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q191-Q196):NEW QUESTION # 191
A US-based mortgage lender has purchased a chatbot. They plan to have the chatbot collect information from consumers who are interested in loans and offer the consumers 2-3 different options based on its current pricing and product offerings, which change frequently. This chatbot was initially developed and previously deployed by a Russian airline for booking flights. The best option for the part of the process that generates the loan offers is:
  • A. Expert System.
  • B. Multimodal Generative AI.
  • C. Retrieval-Augmented Generation.
  • D. Quantum computing.
Answer: A
Explanation:
Generating loan offers based on frequently changing pricing and product rules requires deterministic, rule-based logic to ensure accuracy, compliance, and consistency. An expert system is best suited for this task because it applies explicit business rules rather than probabilistic text generation.

NEW QUESTION # 192
CASE STUDY
A global marketing agency is adapting a large language model ("LLM") to generate content for an upcoming marketing campaign for a client's new product: a hard hat designed for construction workers of any gender to better protect them from head injuries.
The marketing agency is accessing the LLM through an application programming interface ("API") developed by a third-party technology company. They want to generate text to be used for targeted advertising communications that highlight the benefits of the hard hat to potential purchasers. Both the marketing agency and the technology company have taken reasonable steps to address Al governance.
The marketing company has:
* Entered into a contract with the technology company with suitable representations and warranties.
* Completed an impact assessment on the LLM for this intended use.
* Built technical guidance on how to measure and mitigate bias in the LLM.
* Enabled technical aspects of transparency, explainability, robustness and privacy.
* Followed applicable regulatory requirements.
* Created specific legal statements and disclosures regarding the use of the Al on its client's advertising.
The technology company has:
* Provided guidance and resources to developers to address environmental concerns.
* Build technical guidance on how to measure and mitigate bias in the LLM.
* Provided tools and resources to measure bias specific to the LLM.
* Enabled technical aspects of transparency, explainability, robustness and privacy.
* Mapped and mitigated potential societal harms and large-scale impacts.
* Followed applicable regulatory requirements and industry standards.
* Created specific legal statements and disclosures regarding the LLM. including with respect to IP and rights to data.
The agency has taken governance actions such as:
* Conducting an impact assessment
* Providing legal disclosures
* Enabling bias mitigation and explainability
* Complying with regulatory requirements
Which of the following should be included in the marketing company's disclosures about the use of the LLM EXCEPT?
  • A. Compliance with law
  • B. Intended purpose
  • C. Acknowledgement of limitations
  • D. Proprietary methods
Answer: D
Explanation:
The correct answer is B - Proprietary methods. While transparency is important, organizations are not obligated to disclose proprietary algorithms, methods, or trade secrets in public disclosures.
From the AIGP Body of Knowledge - Transparency & Disclosures:
"AI system users should disclose the purpose, capabilities, limitations, and applicable legal context-but not sensitive IP." AI Governance in Practice Report 2024 (Transparency Section) states:
"Disclosure requirements balance public understanding with the need to protect proprietary business interests.
Proprietary training methods are not expected to be disclosed."
Thus, while it's best practice to disclose the intended purpose, legal compliance, and system limitations, internal proprietary techniques are usually excluded.

NEW QUESTION # 193
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. Cost of alternative mechanisms.
  • C. Industry practice.
  • D. Risk to users.
Answer: B
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 # 194
According to the Singapore Model AI Governance Framework, all of the following are recommended measures to promote the responsible use of AI EXCEPT:
  • A. Adapting the existing governance structure to algorithmic decision-making.
  • B. Establishing communications and collaboration among stakeholders.
  • C. Determining the level of human involvement in algorithmic decision-making.
  • D. Employing human-over-the-loop protocols for high-risk systems.
Answer: D
Explanation:
According to the Singapore Model AI Governance Framework, employing human-over-the-loop protocols is not a recommended measure to promote the responsible use of AI. Instead, the framework suggests determining the appropriate level of human involvement in AI-augmented decision-making based on a risk assessment. This approach allows organizations to decide whether a human should be in the loop, on the loop, or out of the loop, depending on factors such as the potential harm to individuals and the reversibility of decisions. The goal is to minimize risks while maintaining operational feasibility.

NEW QUESTION # 195
What is the primary purpose of an AI impact assessment?
  • A. To anticipate and manage the potential risks and harms of an AI system.
  • B. To determine whether a conformity assessment is needed.
  • C. To identify and measure the benefits of an AI system.
  • D. To escalate the findings to the appropriate owner(s).
Answer: A
Explanation:
The primary purpose of an AI impact assessment is to proactively anticipate, identify, and manage potential risks and harms associated with the deployment of an AI system.

NEW QUESTION # 196
......
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