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IAPP AIGP Exam Syllabus Topics:

SectionWeightObjectives
Foundational Concepts of AI Governance24–28%- Fundamental AI definitions, types and characteristics
- Principles of responsible, ethical and trustworthy AI
- Impacts, risks and benefits of AI systems
- Governance frameworks and core concepts
Governance of AI Development21–25%- Testing, validation, documentation and transparency
- Model management, version control and quality assurance
- Requirements gathering, risk assessment and mitigation
- Governance through design and lifecycle management
Governance of AI Deployment and Use21–25%- Implementation, monitoring and ongoing oversight
- Incident response, accountability and audit
- Selection, procurement and third-party management
- Lifecycle maintenance, decommissioning and updates
Laws, Regulations, Standards and Frameworks24–28%- Global and regional regulations (EU AI Act, US, etc.)
- Alignment with data protection and privacy laws
- Sector-specific requirements and compliance obligations
- International standards (ISO 42001, NIST AI RMF, etc.)

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IAPP Certified Artificial Intelligence Governance Professional AIGP Prüfungsfragen mit Lösungen (Q14-Q19):

14. Frage
All of the following types of testing can help evaluate the performance of a responsible Al system EXCEPT?

Antwort: A

Begründung:
Risk probability/severity testing is not typically used to evaluate the performance of an AI system. While important for risk management, it does not directly assess an AI system's operational performance.
Adversarial robustness, statistical sampling, and decision analysis are all methods that can help evaluate the performance of a responsible AI system by testing its resilience, accuracy, and decision-making processes under various conditions. Reference: AIGP Body of Knowledge on AI Performance Evaluation and Testing.


15. Frage
When assessing the success of an AI system in meeting its objectives, which of the following approaches best aligns with the requirement to ensure a comprehensive evaluation while avoiding automation bias?

Antwort: C


16. Frage
CASE STUDY
Please use the following answer the next question:
XYZ Corp., a premier payroll services company that employs thousands of people globally, is embarking on a new hiring campaign and wants to implement policies and procedures to identify and retain the best talent. The new talent will help the company's product team expand its payroll offerings to companies in the healthcare and transportation sectors, including in Asia.
It has become time consuming and expensive for HR to review all resumes, and they are concerned that human reviewers might be susceptible to bias.
Address these concerns, the company is considering using a third-party Al tool to screen resumes and assist with hiring. They have been talking to several vendors about possibly obtaining a third-party Al-enabled hiring solution, as long as it would achieve its goals and comply with all applicable laws.
The organization has a large procurement team that is responsible for the contracting of technology solutions. One of the procurement team's goals is to reduce costs, and it often prefers lower-cost solutions. Others within the company are responsible for integrating and deploying technology solutions into the organization's operations in a responsible, cost-effective manner.
The organization is aware of the risks presented by Al hiring tools and wants to mitigate them. It also questions how best to organize and train its existing personnel to use the Al hiring tool responsibly. Their concerns are heightened by the fact that relevant laws vary across jurisdictions and continue to change.
All of the following are potential negative consequences created by using the Al tool when making hiring decisions EXCEPT?

Antwort: A

Begründung:
The potential negative consequences of using an AI tool in hiring include reputational harm (A), civil rights violations (B), and discriminatory treatment (C). These issues stem from biases in the AI system or its misuse, which can lead to unfair hiring practices and legal liabilities. Intellectual property infringement (D) is not a typical consequence of using AI in hiring, as it relates to the unauthorized use of protected intellectual property, which is not directly relevant to the hiring process or the potential biases within AI tools.


17. Frage
Scenario:
An organization is planning to deploy a new internal application that uses AI to make automated decisions about individuals. This application will process personal information and may affect individuals' access to certain benefits or opportunities.
Which of the following documents must be updated to ensure transparency?

Antwort: C

Begründung:
The correct answer is D. Transparency obligations under data protection laws, such as GDPR and most AI governance frameworks, require that users whose data is being processed be directly informed.
From the AIGP ILT Guide (Privacy Module):
"The user privacy notice must be updated to explain the nature of automated processing, the logic involved, and the significance and consequences for the data subject." Also, per AI Governance in Practice Report 2024 (Part III):
"Transparency obligations apply throughout the lifecycle of AI... Individuals must be informed about automated decision-making and profiling that may impact them." Unlike internal policies or general privacy notices, the user privacy notice provides direct transparency to the individual data subjects affected by AI processing.


18. Frage
What is the most important purpose of a validation data set when developing a machine learning model?

Antwort: B

Begründung:
The validation dataset is primarily used during training to tune and optimize the model's parameters before final evaluation.


19. Frage
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