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IAPP AIGP Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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 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 4
  • 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.

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q110-Q115):

NEW QUESTION # 110
When should an ethical impact assessment for AI be performed?

Answer: B

Explanation:
Ethical impact assessment should begin early and remain iterative throughout the AI lifecycle, making D correct. Waiting until production, a user threshold, or an actual ethical incident would make the assessment reactive rather than preventive. UNESCO describes ethical impact assessment as an " ethics by design " mechanism covering research, design, development, deployment, use, maintenance, monitoring, and eventual termination, while emphasizing its particular value during early research and design. OECD-listed assessment guidance similarly states that the first assessment should occur during design, with reassessments at development, deployment, and other significant lifecycle stages. NIST ' s AI RMF Playbook also recommends impact assessment at key stages because risks, operating conditions, stakeholders, data, and system capabilities can change over time. Continuous reassessment therefore supports proactive identification and mitigation of emerging harms.


NEW QUESTION # 111
Which risk management framework/guide/standard focuses on value-based engineering methodology?

Answer: D

Explanation:
The IEEE 7000-2021 Standard focuses on a value-based engineering methodology for addressing ethical concerns during system design. This standard guides engineers and organizations in integrating ethical considerations into the design and development processes of AI systems, ensuring that these technologies are developed responsibly and align with human values. Reference: AIGP Study Material, section on risk management frameworks and standards.


NEW QUESTION # 112
To maintain fairness in a deployed system, it is most important to:

Answer: D

Explanation:
Monitoring for data drift is critical to maintain fairness, as shifts in data over time can degrade model performance and introduce bias.


NEW QUESTION # 113
The White House Executive Order from November 2023 requires companies that develop dual- use foundation models to provide reports to the federal government about all of the following EXCEPT:

Answer: C

Explanation:
Under the White House Executive Order on Artificial Intelligence (EO 14110), companies developing dual-use foundation models are required to report specific information to the federal government. These requirements include:
1. Ongoing or planned activities related to training, developing, or producing dual-use foundation models, including physical and cybersecurity protections taken to assure the integrity of the training process against sophisticated threats.
2. Ownership and possession of the model weights of any dual-use foundation models, and the physical and cybersecurity measures taken to protect those model weights.
3. The results of any developed dual-use foundation model's performance in relevant AI red-team testing, including a description of any associated measures the company has taken to meet safety objectives, such as mitigations to improve performance on these red-team tests and strengthen overall model security.
4. Other information pertaining to the safety and reliability of dual-use foundation models, or activities or risks that present concerns to U.S. national security.
Notably, the EO does not mandate companies to conduct or report on environmental impact studies for each dual-use foundation model. Therefore, option C is not a required reporting obligation under the Executive Order.


NEW QUESTION # 114
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?

Answer: B

Explanation:
Once a company moves from being adeployerto also acting as aprovider or developer, it assumesnew obligationsunder regulations like the EU AI Act. One of the core requirements for providers is to produce and maintaintechnical documentation, including descriptions of the model, associated risks, and mitigation strategies.
From theAI Governance in Practice Report 2024:
"Providers of high-risk AI systems must draw up technical documentation demonstrating the system's conformity with the requirements... including potential risks and safeguards applied." (p. 34)
"This documentation must be available before placing the system on the market." (p. 35)


NEW QUESTION # 115
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