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IAPP AIGP Exam Syllabus Topics:

SectionObjectives
AI Risk Management- Risk Frameworks and Standards
  • 1. ISO 31000 Risk Management
  • 2. NIST AI Risk Management Framework (RMF)
- Operationalizing Risk Management
  • 1. Risk identification and assessment
  • 2. Risk mitigation strategies
AI Governance Management- Emerging Issues
  • 1. Future Trends
  • 2. Generative AI
  • 3. Ethical AI
- Life Cycle Management
  • 1. Third-party management
  • 2. Auditing and Monitoring
  • 3. Incident Management
AI Governance Implementation- Organizational Governance
  • 1. Roles and Responsibilities (RACI)
  • 2. Governance Structures
  • 3. Policies and Procedures
- Data Governance for AI
  • 1. Data Quality and Integrity
  • 2. Data Privacy and Protection
AI Laws, Regulations, and Standards- Global AI Frameworks
  • 1. UNESCO AI Ethics
  • 2. OECD AI Principles
  • 3. ISO/IEC Standards
- Regional and National Regulations
  • 1. EU AI Act
  • 2. US State and Federal Regulations
  • 3. National AI Strategies
Foundations of AI Governance- AI Governance Fundamentals
  • 1. Key AI Terminology and Concepts
  • 2. Defining AI and its different approaches
  • 3. Understanding the AI Development Life Cycle
- Impacts of AI
  • 1. Benefits of AI
  • 2. Risks of AI

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IAPP Certified Artificial Intelligence Governance Professional AIGP Prüfungsfragen mit Lösungen (Q17-Q22):

17. Frage
Scenario:
A public sector agency is reviewing proposed AI use cases for improving services. It wants to prioritize implementations that deliver value but minimize unintended negative consequences.
When evaluating which AI use cases to implement, an organization should consider all of the following EXCEPT:

Antwort: C

Begründung:
The correct answer is A. While TEVV is important in later lifecycle phases, it is not the primary consideration when evaluating and prioritizing use cases.
From the AIGP Body of Knowledge - Use Case Assessment Module:
"Use case evaluation focuses on value, impact, fairness, and accessibility-technical testing considerations come later." ILT Guide confirms:
"Organizations should first assess whether the AI system provides equitable outcomes and aligns with stakeholder expectations. TEVV is part of implementation, not initial prioritization." Thus, A is not a top-level consideration during use case selection.


18. Frage
CASE STUDY
Please use the following to answer the next question:
A company is considering the procurement of an AI system designed to enhance the security of IT infrastructure. The AI system analyzes how users type on their laptops, including typing speed, rhythm and pressure, to create a unique user profile. This data is then used to authenticate users and ensure that only authorized personnel can access sensitive resources.
When prioritizing the updates to its policies, rules and procedures to include the new AI system for user authentication, the organization should:

Antwort: D

Begründung:
Since the AI system processes personal behavioral data (typing patterns) for authentication, the organization must ensure that this personal data is processed only for specific and lawful purposes, aligning with data protection principles.


19. Frage
Each of the following actors are typically engaged in the Al development life cycle EXCEPT?

Antwort: C


20. Frage
A hospital implements an AI system to assist doctors in diagnosing diseases based on historical patient data. Which one of the following model types best describes this system?

Antwort: C

Begründung:
The AI system uses historical patient data to assess probabilities and uncertainties in diagnosing diseases, which aligns with a probabilistic model.


21. Frage
CASE STUDY
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.
To 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 deploy 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 AI tool to help make hiring decisions EXCEPT?

Antwort: A

Begründung:
The correct answer isB. "Candidate quality" isnota negative consequence of using AI-rather, it is the intendedbenefitof using such tools (e.g., more efficient filtering of strong candidates).
From the AIGP ILT Guide:
"Automation bias, disparate impact, and privacy risks are well-documented concerns in AI-assisted hiring. These risks may arise when AI models replicate biases present in training data or obscure the decision logic." AI Governance in Practice Report 2025 (Bias and Fairness Section) also warns:
"Improper AI use in hiring can lead to disparate impact, where neutral criteria disproportionately disadvantage protected groups." Candidate quality is agoal, not a risk, makingB the correct answerfor what isnota negative outcome.


22. Frage
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