IAPP AIGP Valid Test Syllabus - Reliable AIGP Test Questions

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IAPP AIGP Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 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 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.

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q70-Q75):

NEW QUESTION # 70
All of the following are required for high-risk AI systems under the EU AI Act EXCEPT?

A. Retaining system-generated logs for at least six months.
B. Conducting post-market monitoring.
C. Conducting a conformity assessment.
D. Publishing a detailed report on the training data used.

Answer: D

Explanation:
The EU AI Act imposes severalmandatory obligationson high-risk AI systems, butpublishing a detailed report on training dataisnotone of them.
From theAI Governance in Practice Report 2024:
"It mandates drawing up technical documentation for high-risk AI systems, and requires high-risk AI systems to come with instructions for use that disclose various information, including characteristics, capabilities and performance limitations." (p. 34)
"To make high-risk AI systems more traceable, it also requires AI systems to be able to automatically allow for the maintenance of logs throughout the AI life cycle."
"Conducting post-market monitoring" and "conformity assessments" areexplicitrequirements for high-risk systems. (p. 34-35) However,publishingdetailed training data is typicallyrequired only for general-purpose AI systems with systemic risk, not standard high-risk AI systems.
* A. Log retention,B. Post-market monitoring, andC. Conformity assessmentsareall requiredunder the EU AI Act for high-risk systems.

NEW QUESTION # 71
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:

A. The physical and cybersecurity protection measures of their dual-use foundation models.
B. Any environmental impact study for each dual-use foundation model.
C. Any current training or development of dual-use foundation models.
D. The results of red-team testing of each dual-use foundation model.

Answer: B

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 # 72
CASE STUDY
Please use the following to answer the next question:
A small local flower delivery company operates a few stores and has a limited IT budget. To reduce the time spent on customer service, which is a major drain on employee time, the company plans to implement a simple but high-performance generative AI chatbot on its website. The chatbot will provide real-time, fact-based responses to customer inquiries and assist with order processing, helping to reduce incoming phone calls.
The company currently uses a single on-premises server for its order database and email system and has not yet partnered with a cloud provider.
An internal data privacy policy governs the use of customer dat
a. This policy, written before the adoption of AI, allows the use or transfer of customer data beyond name and contact information but requires that all such data be deleted after the order is completed. The company prefers to maintain this policy without changes.
MULTI-SELECT
Please select 3 of the 5 options below. No partial credit will be given.
Which of the following actions would necessitate a change to the company's privacy policy?

A. The flower shop transfers customer data to the third-party API running the chatbot so that the chatbot service can work as intended during each user session.
B. The chatbot stores inputs for use in Retrieval-Augmented Generation (RAG), but does not use those inputs for retraining the AI model.
C. Programming the chatbot to request the customer's name, telephone number, and address for order deliveries and keeping that data until after delivery of the product has been confirmed.
D. Using data from each customer session with the chatbot for purposes of retraining the underlying model but deleting that data after each customer order is completed.
E. The chatbot deployed on the company's website also scans the customer's appearance during use for signs of frustration or confusion while using the website.

Answer: B,D,E

Explanation:
A, D, and E introduce processing materially different from the practices described in the existing privacy policy. Storing chatbot inputs for RAG creates an additional retention and reuse purpose that should be addressed through appropriate privacy disclosures and retention controls. Using customer-session information to retrain the underlying model creates a distinct secondary purpose beyond processing an order, even when the data is subsequently deleted. Scanning a customer's appearance to infer frustration or confusion introduces an entirely new category of observation and inference, requiring additional transparency, legal-basis analysis, proportionality assessment, and safeguards. By contrast, B involves transferring customer information to a service provider so the requested service can operate, which the existing policy already permits. C involves ordinary contact and delivery information retained through completion of the transaction, which also fits the stated policy.

NEW QUESTION # 73
The benefit of having a clear process for handling AI-related incidents is that it reduces?

A. Documentation requirements.
B. Model failures.
C. Compliance issues.
D. Response times.

Answer: D

Explanation:
The correct answer is A because having a well-defined incident management process enables organizations to respond quickly and effectively when AI-related issues arise. AI governance frameworks emphasize incident management plans as a key component of operational governance, ensuring that risks such as system failures, harmful outputs, or security breaches are promptly identified, escalated, and resolved. A structured process reduces delays by clearly defining roles, responsibilities, and response procedures, thereby minimizing potential harm and operational disruption. While incident processes may also indirectly support compliance and reduce the impact of failures, their primary benefit is improving responsiveness and coordination.
Efficient response times are critical in maintaining trust, ensuring safety, and limiting negative consequences in real-world AI deployments.

NEW QUESTION # 74
What is the most important reason for requiring collaboration among cross-functional stakeholder teams during the AI development lifecycle?

A. To minimize potential liability to users.
B. To establish accountability
C. To minimize the involvement of third parties.
D. To establish a user-centric design.

Answer: B

Explanation:
Collaboration among cross-functional teams ensures clear accountability across different AI development stages, improving governance and risk management.

NEW QUESTION # 75
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