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IAPP AIGP Exam Overview:

Certification Vendor:IAPP (International Association of Privacy Professionals)
Exam Name:IAPP Certified Artificial Intelligence Governance Professional (AIGP) Exam
Exam Number:AIGP
Exam Price:USD 799 (non-member) / USD 649 (IAPP member)
Exam Duration:165 minutes
Exam Format:Scenario-based questions, Multi-select, Multiple-choice, Single-select
Related Certifications:CIPP/US
CIPT
CIPM
CIPP/E
Certificate Validity Period:2 years
Real Exam Qty:100 (85 scored + ~15 unscored pilot questions)
Available Languages:English
Passing Score:300 (scaled score out of 100–500)
Recommended Training:AIGP Practice Exam (Official IAPP Store)
IAPP Official AIGP Training and Resources
Exam Registration:Pearson VUE Scheduling Portal (via IAPP account)
Official IAPP AIGP Exam Registration
Sample Questions:IAPP AIGP Sample Questions
Exam Way:Computer-based exam delivered via Pearson VUE (test center or online proctored OnVUE)
Pre Condition:None
Official Syllabus URL:https://iapp.org/certify/aigp

>> Latest AIGP Study Materials <<

Latest AIGP Study Materials - Quiz AIGP IAPP Certified Artificial Intelligence Governance Professional First-grade Certification Exam Cost

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IAPP AIGP Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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 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 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.

IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q89-Q94):

NEW QUESTION # 89
All of the following are examples of biometric data in the US EXCEPT:

Answer: D

Explanation:
GPS location data is not considered biometric data in the US. Biometric data involves measurements of physical or behavioral characteristics such as iris scans, gait, or keystroke dynamics.


NEW QUESTION # 90
The OECD's Ethical Al Governance Framework is a self-regulation model that proposes to prevent societal harms by?

Answer: A

Explanation:
The OECD's Ethical AI Governance Framework aims to ensure that AI development and deployment are carried out ethically while fostering innovation. The framework includes principles like transparency, accountability, and human rights protections to prevent societal harm. It does not focus solely on technical design or post-deployment monitoring (C), nor does it establish industry-specific requirements (B). While explainability is important, the primary goal is to balance innovation with ethical considerations (D).


NEW QUESTION # 91
CASE STUDY
Please use the following to answer the next question:
A leading insurance provider that offers a range of coverage options to individuals has decided to utilize AI to streamline and improve its customer acquisition and underwriting process, including the accuracy and efficiency of pricing policies. The company has engaged a cloud provider to utilize and fine-tune its pre-trained, general purpose large language model ("LLM").
The company 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 to a human underwriter for final review.
The company 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. They have 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, the company realizes that the LLM declines a higher percentage of women's applications.
The best approach to enable a customer who wants information on the AI model's parameters for underwriting purposes is to provide:

Answer: B

Explanation:
Providing a transparency notice informs customers about how the AI model's parameters affect underwriting decisions, meeting regulatory and ethical requirements for explainability.


NEW QUESTION # 92
According to the GDPR, an individual has the right to have a human confirm or replace an automated decision unless that automated decision:

Answer: C

Explanation:
GDPR permits automated decisions without human intervention if authorized by EU law and accompanied by appropriate safeguards protecting the individual's rights.


NEW QUESTION # 93
The OECD's Ethical AI Governance Framework is a self-regulation model that proposes to prevent societal harms by:

Answer: A

Explanation:
The OECD's Ethical AI Governance Framework emphasizes balancing innovation with ethical considerations to prevent societal harms through responsible AI governance.


NEW QUESTION # 94
......

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