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IAPP AIGP Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 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 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.

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Free PDF AIGP - Updated IAPP Certified Artificial Intelligence Governance Professional Related Exams

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q209-Q214):

NEW QUESTION # 209
Which of the following elements of feature engineering is most important to mitigate the potential bias in an AI system?

A. Feature selection.
B. Feature transformation.
C. Feature validation.
D. Feature importance analysis.

Answer: A

Explanation:
Feature selection is crucial to mitigate bias by carefully choosing attributes that do not introduce unfair or discriminatory information into the AI model.

NEW QUESTION # 210
Which of the following Al uses is best described as human-centric?

A. Machine learning is used for demand forecasting and inventory management, ensuring that consumers can find products they want when they want them.
B. Autonomous robots are used to move products within a warehouse, allowing human workers to reduce physical strain and alleviate monotony.
C. Virtual assistants are used adapt educational content and teaching methods to individuals, offering personalized recommendations based on ability and needs.
D. Pattern recognition algorithms are used to improve the accuracy of weather predictions, which benefits many industries and everyday life.

Answer: C

Explanation:
Human-centric AI focuses on improving the human experience by addressing individual needs and enhancing human capabilities. Option D exemplifies this by using virtual assistants to tailor educational content to each student's unique abilities and needs, thereby supporting personalized learning and improving educational outcomes. This use case directly benefits individuals by providing customized assistance and adapting to their learning pace and style, aligning with the principles of human-centric AI.
Reference: AIGP BODY OF KNOWLEDGE, sections on trustworthy AI and human-centric AI principles.

NEW QUESTION # 211
ISO 42001 International Standard offers guidance for organizations to develop trustworthy AI management systems by:

A. Explicitly over-riding previously issued and now outdated ISO standards.
B. Requiring specific minimum parameters for key suppliers and key aspects of AI management systems.
C. Requiring organizations to continuously improve the effectiveness of their AI management systems.
D. Focusing on high-risk aspects of development of AI management systems.

Answer: C

NEW QUESTION # 212
Which of the following is an example of a high-risk application under the EU Al Act?

A. A government-run social scoring tool.
B. An Al-enabled inventory management tool.
C. A resume scanning tool that ranks applicants.
D. A customer service chatbot tool.

Answer: A

Explanation:
The EU AI Act categorizes certain applications of AI as high-risk due to their potential impact on fundamental rights and safety. High-risk applications include those used in critical areas such as employment, education, and essential public services. A government-run social scoring tool, which assesses individuals based on their social behavior or perceived trustworthiness, falls under this category because of its profound implications for privacy, fairness, and individual rights. This contrasts with other AI applications like resume scanning tools or customer service chatbots, which are generally not classified as high-risk under the EU AI Act.

NEW QUESTION # 213
Before training an AI model, which activity best supports governance and risk mitigation?

A. Deploying the model in a test environment
B. Selecting the largest available dataset
C. Publishing a transparency notice
D. Performing an AI impact assessment

Answer: D

NEW QUESTION # 214
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