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Exam AIGP PDF | AIGP Certification Sample Questions

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IAPP AIGP Exam Syllabus Topics:

Topic
Details

Topic 1

Contemplating Ongoing Issues and Concerns: The topic focuses on issues around AI governance.

Topic 2

Understanding the Foundations of Artificial Intelligence: This topic defines AI and machine learning. It also provides an overview of the different types of AI systems and their use cases.

Topic 3

Implementing Responsible AI Governance and Risk Management: It explains the collaboration of major AI stakeholders in a layered approach.

Topic 4

Understanding AI Impacts and Responsible AI Principles: This topic identifies different risks that that ungoverned AI systems. The topic also describes features and principles that are essential for trustworthy and ethical AI.

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100% Pass 2025 IAPP AIGP: IAPP Certified Artificial Intelligence Governance Professional Perfect Exam PDF

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q121-Q126):

NEW QUESTION # 121
What is the primary purpose of an Al impact assessment?

A. To identify and measure the benefits of an Al system.
B. Anticipate and manage the potential risks and harms of an Al system.
C. To define and evaluate the legal risks associated with developing an Al system.
D. To define and document the roles and responsibilities of Al stakeholders.

Answer: B

Explanation:
The primary purpose of an AI impact assessment is to anticipate and manage the potential risks and harms of an AI system. This includes identifying the possible negative outcomes and implementing measures to mitigate these risks. This process helps ensure that AI systems are developed and deployed in a manner that is ethically and socially responsible, addressing concerns such as bias, fairness, transparency, and accountability. The assessment often involves a thorough evaluation of the AI system's design, data inputs, outputs, and the potential impact on various stakeholders. This approach is crucial for maintaining public trust and adherence to regulatory requirements.

NEW QUESTION # 122
According to the GDPR, what is an effective control to prevent a determination based solely on automated decision-making?

A. Provide a right to review automated decision.
B. Define suitable measures to safeguard personal data.
C. Provide a just-in-time notice about the automated decision-making logic.
D. Establish a human-in-the-loop procedure.

Answer: D

Explanation:
The GDPR requires that individuals have the right to not be subject to decisions based solely on automated processing, including profiling, unless specific exceptions apply. One effective control is to establish a human-in-the-loop procedure (D), ensuring human oversight and the ability to contest decisions. This goes beyond just-in-time notices (A), data safeguarding (B), or review rights (C), providing a more robust mechanism to protect individuals' rights.

NEW QUESTION # 123
The processes and methods that allow human users to understand and trust the outputs produced by AI are important in addressing which key regulatory concern?

A. Responsible AI
B. Explainable AI
C. Trustworthy AI
D. Interpretable AI

Answer: B

Explanation:
The correct answer is Explainable AI because it specifically refers to the ability of a system to describe the logic behind its decisions or outputs in a way that is understandable to humans. This is a key part of regulatory and ethical frameworks and is directly related to addressing the black-box problem in AI.
From the AIGP ILT Participant Guide (Module on Transparency and Explainability):
"Explainability refers to the understanding of how a black-box model works. The black-box problem exists because some models are too complex for human interpretation. Explainability methods aim to provide meaningful insight into the logic and decision-making of AI systems." Also, according to the AI Governance in Practice Report 2024:
"Explainability refers to the representation of the underlying mechanisms of the AI system's operation... a key tenet of AI governance due to the desire to understand how AI systems are built, managed and maintained." Thus, while Trustworthy and Responsible AI are broader concepts, explainability specifically targets the regulatory concern about understanding outputs.

NEW QUESTION # 124
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. Input data, to ensure the ads are reaching the target audience.
C. GPU performance, to evaluate the tool's robustness.
D. Output data, assess the delta between the prediction and actual ad clicks.

Answer: D

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 # 125
Scenario:
A public sector agency is reviewing proposed AI use cases for improving services. It wants to prioritize implementations that deliver value but minimize unintended negative consequences.
When evaluating which AI use cases to implement, an organization should consider all of the following EXCEPT:

A. Potential positive and negative impacts of the system
B. The users and their expectations
C. Equitable access to the AI tool
D. Related TEVV (test, evaluate, verify, validate) and system metrics

Answer: D

Explanation:
The correct answer is A. While TEVV is important in later lifecycle phases, it is not the primary consideration when evaluating and prioritizing use cases.
From the AIGP Body of Knowledge - Use Case Assessment Module:
"Use case evaluation focuses on value, impact, fairness, and accessibility-technical testing considerations come later." ILT Guide confirms:
"Organizations should first assess whether the AI system provides equitable outcomes and aligns with stakeholder expectations. TEVV is part of implementation, not initial prioritization." Thus, A is not a top-level consideration during use case selection.

NEW QUESTION # 126
......

With the ever-increasing competition, people take IAPP AIGPcertification to exhibit their experience, skills, and abilities in a better way. Having IAPP Certified Artificial Intelligence Governance Professional AIGP certificate shows that you have better exposure than others. So, AIGP Certification also gives you an advantage in the industry when employers seek candidates for job opportunities. However, preparing for the IAPP AIGP exam can be a difficult and time-consuming process.

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