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IAPP AIGP Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Governance of AI Development	21–25%	- Testing, validation, documentation and transparency - Governance through design and lifecycle management - Requirements gathering, risk assessment and mitigation - Model management, version control and quality assurance
Topic 2: Governance of AI Deployment and Use	21–25%	- Incident response, accountability and audit - Lifecycle maintenance, decommissioning and updates - Selection, procurement and third-party management - Implementation, monitoring and ongoing oversight
Topic 3: Laws, Regulations, Standards and Frameworks	24–28%	- International standards (ISO 42001, NIST AI RMF, etc.) - Global and regional regulations (EU AI Act, US, etc.) - Alignment with data protection and privacy laws - Sector-specific requirements and compliance obligations
Topic 4: Foundational Concepts of AI Governance	24–28%	- Principles of responsible, ethical and trustworthy AI - Impacts, risks and benefits of AI systems - Governance frameworks and core concepts - Fundamental AI definitions, types and characteristics

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q136-Q141):

NEW QUESTION # 136
What is the primary objective of continuous monitoring in the lifecycle of an AI tool?

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

Answer: B

Explanation:
The correct answer is B because continuous monitoring is a core component of AI governance that ensures systems remain effective, reliable, and aligned with their intended objectives over time. AI systems can degrade due to data drift, model drift, or changing real-world conditions, making ongoing performance tracking essential. Monitoring allows organizations to detect anomalies, biases, or performance issues and take corrective actions such as retraining or recalibration. Governance frameworks emphasize post- deployment oversight to ensure systems continue to operate safely and within acceptable risk thresholds.
Option A incorrectly suggests fully autonomous evolution without oversight, which contradicts governance principles. Options C and D address specific operational concerns but do not capture the primary purpose of continuous monitoring, which is maintaining performance, accountability, and alignment with defined goals.

NEW QUESTION # 137
All of the following are elements of establishing a global Al governance infrastructure EXCEPT?

A. Creating policies and procedures to manage third-partyrisk.
B. Providing training to foster a culture that promotes ethical behavior.
C. Publicly disclosing ethical principles.
D. Understanding differences in norms across countries.

Answer: C

Explanation:
Establishing a global AI governance infrastructure involves several key elements, including providing training to foster a culture that promotes ethical behavior, creating policies and procedures to manage third-party risk, and understanding differences in norms across countries. While publicly disclosing ethical principles can enhance transparency and trust, it is not a core element necessary for the establishment of a governance infrastructure. The focus is more on internal processes and structures rather than public disclosure. Reference: AIGP Body of Knowledge on AI Governance and Infrastructure.

NEW QUESTION # 138
Which of the following best describes the data minimization principle as it relates to an AI model?

A. Include techniques such as adding noise or using synthetic data.
B. Only use personal data during the inference phase.
C. Review all the data manually.
D. Avoid training the model on personal data.

Answer: A

Explanation:
A best reflects practical application of data minimization to machine learning. Data minimization requires personal data to be adequate, relevant, and limited to what is necessary for the specified purpose. AI development does not categorically prohibit using personal data in training, so B is too absolute. Personal data may legitimately be required during both training and inference, making D incorrect. Manual review of every data item is neither the definition nor a necessary implementation of minimization. Privacy-enhancing techniques can instead reduce the amount or identifiability of personal data processed while retaining model utility. ICO AI guidance specifically identifies perturbation or adding noise, synthetic data, and federated learning as techniques that can support data minimization during model training. Thus, A is the technically and governance-aligned choice.

NEW QUESTION # 139
Which of the following Al uses is best described as human-centric?

A. Autonomous robots are used to move products within a warehouse, allowing human workers to reduce physical strain and alleviate monotony.
B. Machine learning is used for demand forecasting and inventory management, ensuring that consumers can find products they want when they want them.
C. Virtual assistants are used adapt educational content and teaching methods to individuals, offering personalized recommendations based on ability and needs.
D. Pattern recognition algorithms are used to improve the accuracy of weather predictions, which benefits many industries and everyday life.

Answer: C

Explanation:
Human-centric AI focuses on improving the human experience by addressing individual needs and enhancing human capabilities. Option D exemplifies this by using virtual assistants to tailor educational content to each student's unique abilities and needs, thereby supporting personalized learning and improving educational outcomes. This use case directly benefits individuals by providing customized assistance and adapting to their learning pace and style, aligning with the principles of human-centric AI.

NEW QUESTION # 140
According to the GDPR, what is an effective control to prevent a determination based solely on automated decision-making?

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

Answer: A

Explanation:
GDPR requires effective controls like human-in-the-loop procedures to prevent decisions based solely on automated processing without human intervention.

NEW QUESTION # 141
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