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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 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 3	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 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.

Reference: https://iapp.org/certify/aigp/

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions:

Question #1

Scenario:
A financial services company is planning a new AI project to assess creditworthiness. The AI team is mapping out what tasks should be completed during theplanning phaseof the AI lifecycle.
The planning phase of the AI lifecycle includes all of the following EXCEPT:

A. Choice of the architecture
B. Definition of underlying assumptions
C. Context in which the model will operate
D. Approach to governance

Reveal Solution Discussion 0

Correct Answer: A 🗳️

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Question #2

Scenario:
A global organization wants to align with international frameworks on AI governance. They are reviewing guidance from the OECD on how to incorporate broader governance tools into their AI program.
Codes of conductandcollective agreementsare what type of assessment tools as defined by theOrganization for Economic Cooperation and Development (OECD)?

A. Educational
B. Procedural
C. Technical
D. Analytic

Reveal Solution Discussion 0

Correct Answer: B 🗳️

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Question #3

CASE STUDY
Please use the following answer the next question:
A mid-size US healthcare network has decided to develop an Al solution to detect a type of cancer that is most likely arise in adults. Specifically, the healthcare network intends to create a recognition algorithm that will perform an initial review of all imaging and then route records a radiologist for secondary review pursuant agreed-upon criteria (e.g., a confidence score below a threshold).
To date, the healthcare network has taken the following steps: defined its Al ethical principles: conducted discovery to identify the intended uses and success criteria for the system: established an Al governance committee; assembled a broad, crossfunctional team with clear roles and responsibilities; and created policies and procedures to document standards, workflows, timelines and risk thresholds during the project.
The healthcare network intends to retain a cloud provider to host the solution and a consulting firm to help develop the algorithm using the healthcare network's existing data and de-identified data that is licensed from a large US clinical research partner.
Which stakeholder group is most important in selecting the specific type of algorithm?

A. The consulting firm.
B. The cloud provider.
C. The healthcare network's Al governance committee.
D. The healthcare network'sdata science team.

Reveal Solution Discussion 0

Correct Answer: D 🗳️

Question #4

What is the 1956 Dartmouth summer research project on Al best known as?

A. A research project to create a test for machine intelligence.
B. A meeting focused on the impacts of the launch of the first mass-produced computer.
C. A research project on the impacts of technology on society.
D. A meeting focused on the founding of the Al field.

Reveal Solution Discussion 0

Correct Answer: D 🗳️

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Question #5

CASE STUDY
Please use the following to answer the next question:
A mid-size US healthcare network has decided to develop an AI solution to detect a type of cancer that is most likely to arise in adults. Specifically, the healthcare network intends to create a recognition algorithm that will perform an initial review of all imaging and then route records to a radiologist for secondary review pursuant to agreed-upon criteria such as a confidence score below a threshold.
To date, the healthcare network has:
Defined its AI ethical principles
Conducted discovery to identify the intended uses and success criteria for the system Established an AI risk committee Assembled a cross-functional team with clear roles and responsibilities Created policies and procedures to document standards, workflows, timelines and risk thresholds during the project The healthcare network intends to retain a cloud provider to host the solution. It also intends to retain a large consulting firm to supplement its small data science team and help develop the algorithm using the healthcare network's existing data and de-identified data that is licensed from a large US clinical research partner.
Which of the following steps can best mitigate the possibility of discrimination prior to training and testing the AI solution?