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IAPP AIGP Prüfung Übungen und Antworten

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IAPP AIGP Prüfungsplan:

Thema
Einzelheiten

Thema 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.

Thema 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.

Thema 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.

Thema 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.

>> AIGP Fragenkatalog <<

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IAPP Certified Artificial Intelligence Governance Professional AIGP Prüfungsfragen mit Lösungen (Q191-Q196):

191. Frage
All of the following analyses are part of a deactivating risk strategy EXCEPT:

A. Understanding algorithmic methodology in AI model
B. Understanding regulatory requirements related to data retention.
C. Evaluating business continuity and financial risks.
D. Evaluating up and downstream system dependencies.

Antwort: A

Begründung:
Understanding algorithmic methodology is part of assessing model design and functionality, not typically a focus of deactivating risk strategies, which center on operational, regulatory, and system continuity risks.

192. Frage
Which of the following is an example of a high-risk application under the EU Al Act?

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

Antwort: C

Begründung:
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.

193. Frage
Scenario:
An organization wants to leverage its existing compliance structures to identify AI-specific risks as part of an ongoing data governance audit.
Which of the following compliance-related controls within an organization is most easily adapted to identify AI risks?

A. Privacy impact assessments
B. Transfer risk assessments
C. Privacy training
D. Penetration testing

Antwort: A

Begründung:
The correct answer is D - Privacy impact assessments (PIAs). These are directly adaptable for identifying risks in AI systems, particularly around data usage, bias, and individual impacts.
From the AIGP ILT Guide - Risk Management Module:
"PIAs and DPIAs are existing tools used in privacy compliance that can be extended to evaluate the risks of AI, including fairness, explainability, and legality." AI Governance in Practice Report 2024 further explains:
"Organizations can adapt privacy impact assessments to evaluate the ethical, legal, and technical risks posed by AI systems. They provide a structured and recognized method." PIAs are preferable over general security practices (like pen testing) which do not address algorithmic bias or legal compliance directly.

194. Frage
A US-based mortgage lender has purchased a chatbot. They plan to have the chatbot collect information from consumers who are interested in loans and offer the consumers 2-3 different options based on its current pricing and product offerings, which change frequently. This chatbot was initially developed and previously deployed by a Russian airline for booking flights. The best option for the part of the process that generates the loan offers is:

A. Quantum computing.
B. Retrieval-Augmented Generation.
C. Multimodal Generative AI.
D. Expert System.

Antwort: D

Begründung:
Generating loan offers based on frequently changing pricing and product rules requires deterministic, rule-based logic to ensure accuracy, compliance, and consistency. An expert system is best suited for this task because it applies explicit business rules rather than probabilistic text generation.

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

Antwort: A

Begründung:
Copyright protection typically requires a human author's creative input, so modifying AI-generated images in a creative way demonstrates the artist's originality needed for copyright.

196. Frage
......

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