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IAPP AIGP Exam Syllabus Topics:

Topic	Details
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 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 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 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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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q160-Q165):

NEW QUESTION # 160
A company is creating a mobile app to enable individuals to upload images and videos, and analyze this data using ML to provide lifestyle improvement recommendations. The signup form has the following data fields:
1.First name
2.Last name
3.Mobile number
4.Email ID
5.New password
6.Date of birth
7.Gender
In addition, the app obtains a device's IP address and location information while in use.
What GDPR privacy principles does this violate?

A. Accountability and Lawfulness.
B. Transparency and Accuracy.
C. Purpose Limitation and Data Minimization.
D. Integrity and Confidentiality.

Answer: C

Explanation:
The GDPR privacy principles that this scenario violates are Purpose Limitation and Data Minimization. Purpose Limitation requires that personal data be collected for specified, explicit, and legitimate purposes and not further processed in a manner that is incompatible with those purposes. Data Minimization mandates that personal data collected should be adequate, relevant, and limited to what is necessary in relation to the purposes for which they are processed. In this case, collecting extensive personal information (e.g., IP address, location, gender) and potentially using it beyond the necessary scope for the app's functionality could violate these principles by collecting more data than needed and possibly using it for purposes not originally intended.

NEW QUESTION # 161
What is the best reason for a company adopt a policy that prohibits the use of generative Al?

A. Avoid accidental disclosure to its confidential and proprietary information.
B. Avoid using technology that cannot be monetized.
C. Avoid the time necessary to train employees on acceptable use.
D. Avoid needing to identify and hire qualified resources.

Answer: A

Explanation:
The primary concern for a company adopting a policy prohibiting the use of generative AI is the risk of accidental disclosure of confidential and proprietary information. Generative AI tools can inadvertently leak sensitive data during the creation process or through data sharing. This risk outweighs the other reasons listed, as protecting sensitive information is critical to maintaining the company's competitive edge and legal compliance. This rationale is discussed in the sections on risk management and data privacy in the IAPP AIGP Body of Knowledge.

NEW QUESTION # 162
A company that deploys AI but is not currently a provider or developer intends to develop and market its own AI system.
Which obligation would then be likely to apply?

A. Developing documentation on the system, the potential risks and the safeguards applied.
B. Implementing a risk management framework.
C. Conducting an impact assessment including a post-deployment monitoring plan.
D. Developing a reporting plan for any observed algorithmic discrimination or harms to individuals' rights and freedoms.

Answer: A

Explanation:
Once a company moves from being adeployerto also acting as aprovider or developer, it assumesnew obligationsunder regulations like the EU AI Act. One of the core requirements for providers is to produce and maintaintechnical documentation, including descriptions of the model, associated risks, and mitigation strategies.
From theAI Governance in Practice Report 2024:
"Providers of high-risk AI systems must draw up technical documentation demonstrating the system's conformity with the requirements... including potential risks and safeguards applied." (p. 34)
"This documentation must be available before placing the system on the market." (p. 35)

NEW QUESTION # 163
All of the following may be copyright risks from teachers using generative AI to create course content EXCEPT?

A. Content created by an LLM may be protectable under U.S. intellectual property law.
B. Generative AI is generally trained using intellectual property owned by third parties.
C. Students must expressly consent to this use of generative AI.
D. Generative AI often creates content without attribution.

Answer: C

NEW QUESTION # 164
An artist has been using an Al tool to create digital art and would like to ensure that it has copyright protection in the United States.
Which of the following is most likely to enable the artist to receive copyright protection?

A. Obtain a representation from the Al provider on how the tool works.
B. Update the images in a creative way to demonstrate that it is the artist's.
C. Provide a log of the prompts the artist used to generate the images.
D. Ensure the tool was trained using publicly available content.

Answer: B

Explanation:
For the artist to receive copyright protection, the most effective approach is to demonstrate that the final artwork includes sufficient creative input by the artist. By updating or altering the images in a way that reflects the artist's personal creativity, the artist can claim originality, which is a core requirement for copyright protection under U.S. law. The other options do not directly address the originality and creative input required for copyright. This is highlighted in the sections on copyright protection in the IAPP AIGP Body of Knowledge.

NEW QUESTION # 165
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