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IAPP AIGP Exam Syllabus Topics:

Topic	Details
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 (Q172-Q177):

NEW QUESTION # 172
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 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.
B. 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.
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. The chatbot stores inputs for use in Retrieval-Augmented Generation (RAG), but does not use those inputs for retraining the AI model.
E. 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.

Answer: A,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 # 173
Scenario:
An organization is developing a powerful general-purpose AI (GPAI) model that has systemic impact. The compliance team is assessing what legal obligations apply under the EU AI Act.
Under the EU AI Act, which of the following compliance actions applies only to General Purpose AI models with systemic risk?

A. Maintaining up-to-date technical documentation, including testing details
B. Implementing an intellectual property policy to comply with EU copyright laws
C. Making information available to downstream providers who integrate the model into their AI systems
D. Publishing a detailed summary of the data used to train the model

Answer: D

Explanation:
The correct answer is A. Only GPAI models with systemic risk must publish a detailed summary of training data to meet transparency and accountability standards under the EU AI Act.
From the AI Governance in Practice Report 2024 (EU AI Act Section):
"For GPAI systems with systemic risk, providers must publish sufficiently detailed summaries of the content used to train the model." Also, the AIGP ILT Guide confirms:
"The obligation to disclose summaries of training data applies only to systemic-risk GPAI models, not all general-purpose models or high-risk systems." This unique requirement is part of the Act's effort to increase transparency and auditability for powerful foundational models.

NEW QUESTION # 174
Each of the following actors are typically engaged in the AI development life cycle EXCEPT:

A. Government regulators.
B. Legal and privacy governance experts.
C. Socio-cultural and technical experts.
D. Data architects.

Answer: A

Explanation:
Government regulators oversee compliance but are not typically involved directly in the AI development life cycle.

NEW QUESTION # 175
CASE STUDY
Please use the following to answer the next question:
A company is considering the procurement of an AI system designed to enhance the security of IT infrastructure. The AI system analyzes how users type on their laptops, including typing speed, rhythm and pressure, to create a unique user profile. This data is then used to authenticate users and ensure that only authorized personnel can access sensitive resources.
When prioritizing the updates to its policies, rules and procedures to include the new AI system for user authentication, the organization should:

A. Reduce the complexity of the policy to make it easier for non-technical employees to understand.
B. Ensure that any personal data used is only processed for a specific and lawful purpose.
C. Update security controls for sensitive data.
D. Update third-party data sharing policies.

Answer: B

Explanation:
Since the AI system processes personal behavioral data (typing patterns) for authentication, the organization must ensure that this personal data is processed only for specific and lawful purposes, aligning with data protection principles.

NEW QUESTION # 176
Pursuant to the White House Executive Order of November 2023, who is responsible for creating guidelines to conduct red-teaming tests of AI systems?

A. Department of Homeland Security (DHS).
B. National Science and Technology Council (NSTC).
C. National Institute of Standards and Technology (NIST).
D. Office of Science and Technology Policy (OSTP).

Answer: C

Explanation:
According to the White House Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence (Executive Order 14110), the responsibility for creating guidelines to conduct red-teaming tests of AI systems falls to the National Institute of Standards and Technology (NIST). Specifically, the Executive Order directs NIST to establish guidelines and best practices for developing and deploying safe, secure, and trustworthy AI systems, including the creation of standards and procedures for developers to conduct AI red- teaming tests.

NEW QUESTION # 177
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