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[General] Providing You High Hit Rate Latest Braindumps AIGP Ppt with 100% Passing Guarant

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【General】 Providing You High Hit Rate Latest Braindumps AIGP Ppt with 100% Passing Guarant

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q158-Q163):NEW QUESTION # 158
If it is possible to provide a rationale for a specific output of an Al system, that system can best be described as?
  • A. Explainable.
  • B. Accountable.
  • C. Transparent.
  • D. Reliable.
Answer: A
Explanation:
If it is possible to provide a rationale for a specific output of an AI system, that system can best be described as explainable. Explainability in AI refers to the ability to interpret and understand the decision-making process of the AI system. This involves being able to articulate the factors and logic that led to a particular output or decision. Explainability is critical for building trust, enabling users to understand and validate the AI system's actions, and ensuring compliance with ethical and regulatory standards. It also facilitates debugging and improving the system by providing insights into its behavior.

NEW QUESTION # 159
Your organization is searching for a new way to help accurately forecast sales predictions by various types of customers.
Which of the following is the best type of model to choose if your organization wants to customize the model and avoid lock-in?
  • A. A free large language model.
  • B. A proprietary generative AI model.
  • C. A classic machine learning model.
  • D. A subscription-based, multimodal model.
Answer: C
Explanation:
Forcustomizable, interpretable modelsthat allow organizations toretain control and avoid vendor lock-in, classic ML models(e.g., regression, decision trees, random forests) are optimal.
From theAI Governance in Practice Report 2024:
"Organizations seeking transparency, customizability, and control often prefer classic ML models due to their flexibility and ease of governance." (p. 33)
* AandCmay have limited transparency and are often tied to specific providers.
* Dinvolves ongoing costs and limited model control.

NEW QUESTION # 160
Scenario:
A U.S.-based AI governance professional is evaluating resources from the National Institute of Standards and Technology (NIST) to guide the organization's AI risk assessment strategy. They are particularly interested in programs focused on assessing AI-specific impacts.
The main purpose of NIST'sAssessing Risks and Impacts of AI (ARIA)program is to:
  • A. Provide a suite of resources to manage risks
  • B. Offer a regulatory sandbox for risk reporting
  • C. Promote interoperability across AI systems
  • D. Pilot new standards for AI red-teaming
Answer: A
Explanation:
The correct answer isA. TheARIA programby NIST is explicitly designed tosupport stakeholders in understanding and managing the risks and impactsof AI systems.
From the AIGP ILT Guide - U.S. Risk Frameworks Module:
"NIST's ARIA program develops and pilots assessment tools for AI risks and impacts, aimed at improving organizational capacity for responsible AI use." Also cited in the AI Governance in Practice Report2025(Frameworks Section):
"ARIA supports and aligns with the AI Risk Management Framework by helping organizations assess AI harms, safety concerns, and societal implications." ARIA isnota red-teaming or sandbox program-it's anassessment and governance resource.

NEW QUESTION # 161
You are an engineer that developed an Al-based ad recommendation tool.
Which of the following should be monitored to evaluate the tool's effectiveness?
  • A. Algorithmic patterns, to show the model has a high degree of accuracy.
  • B. GPU performance, to evaluate the tool's robustness.
  • C. Output data, assess the delta between the prediction and actual ad clicks.
  • D. Input data, to ensure the ads are reaching the target audience.
Answer: C
Explanation:
To evaluate the effectiveness of an AI-based ad recommendation tool, the most relevant metric is the output data, specifically assessing the delta between the prediction and actual ad clicks. This metric directly measures the tool's accuracy and effectiveness in making accurate recommendations that lead to user engagement. While monitoring algorithmic patterns and input data can provide insights into the model's behavior and targeting accuracy, and GPU performance can indicate the robustness and efficiency of the tool, the primary indicator of effectiveness for an ad recommendation tool is how well it predicts actual ad clicks.
Reference: AIGP BODY OF KNOWLEDGE, sections on AI performance metrics and evaluation methods.

NEW QUESTION # 162
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. Proprietary methods
  • B. Compliance with law
  • C. Acknowledgement of limitations
  • D. Intended purpose
Answer: A
Explanation:
The correct answer isB - Proprietary methods. While transparency is important, organizations arenot obligated to disclose proprietary algorithms, methods, or trade secretsin 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 Report2025(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 theintended purpose, legal compliance, and system limitations, internal proprietary techniquesare usually excluded.

NEW QUESTION # 163
......
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