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IAPP AIGP Exam Overview:

Certification Vendor:	IAPP
Exam Name:	IAPP Certified Artificial Intelligence Governance Professional
Exam Number:	AIGP
Passing Score:	300
Exam Format:	Multiple-choice
Available Languages:	English
Related Certifications:	CIPP/A CIPT CIPM CIPP/E CIPP/US
Real Exam Qty:	100
Exam Price:	USD 550
Certificate Validity Period:	2 Years
Exam Duration:	150 minutes
Sample Questions:	IAPP AIGP Sample Questions
Exam Way:	Online (OnVUE) or Test Center (Pearson VUE)
Pre Condition:	No specific prerequisites. Recommended background in privacy, compliance, legal, or technology.
Official Syllabus URL:	https://iapp.org/certify/aigp/

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IAPP AIGP 考試大綱：

主題	簡介
主題 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.
主題 2	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.
主題 3	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.
主題 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.

最新的 Artificial Intelligence Governance AIGP 免費考試真題 (Q23-Q28):

問題 #23
An EU bank intends to launch a multi-modal Al platform for customer engagement and automated decision-making assist with the opening of bank accounts. The platform has been subject to thorough risk assessments and testing, where it proves to be effective in not discriminating against any individual on the basis of a protected class.
What additional obligations must the bank fulfill prior to deployment?

A. The bank must subject the Al system an adequacy decision and publish its appropriate safeguards.
B. The bank must disclose the use of the Al system and implement suitable measures for users to contest automated decision-making.
C. The bank must disclose how the Al system works under the Ell Digital Services Act.
D. The bank must obtain explicit consent from users under the privacy Directive.

答案：B

解題說明：
Under the EU regulations, particularly the GDPR, banks using AI for decision-making must inform users about the use of AI and provide mechanisms for users to contest decisions. This is part of ensuring transparency and accountability in automated processing. Explicit consent under the privacy directive (A) and disclosing under the Digital Services Act (B) are not specifically required in this context. An adequacy decision is related to data transfers outside the EU (C).

問題 #24
CASE STUDY
Please use the following answer the next question:
ABC Corp, is a leading insurance provider offering a range of coverage options to individuals. ABC has decided to utilize artificial intelligence to streamline and improve its customer acquisition and underwriting process, including the accuracy and efficiency of pricing policies.
ABC has engaged a cloud provider to utilize and fine-tune its pre-trained, general purpose large language model ("LLM"). In particular, ABC intends to use its historical customer data-including applications, policies, and claims-and proprietary pricing and risk strategies to provide an initial qualification assessment of potential customers, which would then be routed a human underwriter for final review.
ABC and the cloud provider have completed training and testing the LLM, performed a readiness assessment, and made the decision to deploy the LLM into production. ABC has designated an internal compliance team to monitor the model during the first month, specifically to evaluate the accuracy, fairness, and reliability of its output. After the first month in production, ABC realizes that the LLM declines a higher percentage of women's loan applications due primarily to women historically receiving lower salaries than men.
What is the best strategy to mitigate the bias uncovered in the loan applications?

A. Delete all gender-based data in the data set.
B. Retrain the model with data that reflects demographic parity.
C. Document all instances of bias in the data set.
D. Procure a third-party statistical bias assessment tool.

答案：B

解題說明：
Retraining the model with data that reflects demographic parity is the best strategy to mitigate the bias uncovered in the loan applications. This approach addresses the root cause of the bias by ensuring that the training data is representative and balanced, leading to more equitable decision-making by the AI model.

問題 #25
The most important policy to assess the operations of an AI model is to follow the:

A. Acceptable use policy of the model provider.
B. Privacy policy of the model provider.
C. Security policy of the model provider.
D. Code of conduct policy of the model provider.

答案：A

解題說明：
The acceptable use policy defines how the model is permitted to be operated, including restrictions, prohibited behaviors, and required safeguards. It is the most important policy for assessing whether the AI model is being used appropriately and within operational boundaries.

問題 #26
Which of the following is a foundational characteristic of effective AI governance?

A. Reliance on tested vendor management processes.
B. Uniform policies and procedures across developer, deployer and user roles.
C. Thorough reviews of a company's public filings with experts.
D. Engagement of a cross-functional team.

答案：D

解題說明：
Effective AI governance fundamentally requires the engagement of a cross-functional team to incorporate diverse perspectives and expertise throughout the AI lifecycle.

問題 #27
All of the following are required for high-risk AI systems under the EU AI Act EXCEPT?

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

答案：B

解題說明：
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 Report2025:
"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.

問題 #28
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