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AIGP Demotesten, AIGP Echte Fragen
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IAPP AIGP Prüfungsplan:| Thema | Einzelheiten | | Thema 1 | - 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 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 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.
| | Thema 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 AIGP Echte Fragen & AIGP Fragen Und AntwortenWollen Sie durch die IAPP AIGP Zertifizierungsprüfung Ihre Position in der heutigen kunkurrenzfähigen IT-Branche und Ihre beruflichen Fähigkeiten verstärken? Dann müssen Sie mit breiten fachlichen Kenntnissen ausgerüstet sein. Und es ist nicht so einfach, die IAPP AIGP Zertifizierungsprüfung zu bestehen. Vielleicht ist die IAPP AIGP Zertifizierungsprüfung ein Sprungbrett, um im IT-Bereich befördert zu werden. Aber man braucht doch nicht, sich mit so viel Zeit und Energie für die Prüfung verwenden. Sie können unsere It-Pruefung Produkte wählen, die speziellen Schulungsunterlagen für die IT-Zertifizierungsprüfungen bieten.
IAPP Certified Artificial Intelligence Governance Professional AIGP Prüfungsfragen mit Lösungen (Q53-Q58):53. 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.
Which of the following measures should XYZ adopt to best mitigate its risk of reputational harm from using the Al tool?
- A. Direct the procurement team to select the most economical Al tool.
- B. Continue to require XYZ's hiring personnel to manually screen all applicants.
- C. Test the Al tool pre- and post-deployment.
- D. Ensure the vendor assumes responsibility for all damages.
Antwort: C
Begründung:
To mitigate the risk of reputational harm from using an AI hiring tool, XYZ Corp should rigorously test the AI tool both before and after deployment. Pre-deployment testing ensures the tool works correctly and does not introduce bias or other issues. Post-deployment testing ensures the tool continues to operate as intended and adapts to any changes in data or usage patterns. This approach helps to identify and address potential issues proactively, thereby reducing the risk of reputational harm. Ensuring the vendor assumes responsibility for damages (B) does not address the root cause of potential issues, selecting the most economical tool (C) may compromise quality, and continuing manual screening (D) defeats the purpose of using the AI tool.
54. Frage
A leading software development company wants to integrate AI-powered chatbots into their customer service platform. After researching various AI models in the market which have been developed by third-party developers, they're considering two options:
Option A - an open-source language model trained on a vast corpus of text data and capable of being trained to respond to natural language inputs.
Option B - a proprietary, generative AI model pre-trained on large data sets, which uses transformer-based architectures to generate human-like responses based on multimodal user input.
Option A would be the best choice for the company because?
- A. It is built for large-scale, complex dialogues and would be more effective in handling high-volume customer inquiries.
- B. It is less expensive to run
- C. It may be better suited for applications requiring customization.
- D. It can handle voice commands and is more suitable for phone-based customer support.
Antwort: C
Begründung:
Open-source modelsoffer morecustomization flexibility, allowing organizations to fine-tune or adapt the model tofit their own workflows, branding, or compliance needs- making it preferable when deep control is needed.
From theAI Governance in Practice Report2025:
"Open-source AI allows organizations to review, adapt, and control model behavior in line with organizational needs and policies." (p. 39)
55. Frage
Under the NIST Al Risk Management Framework, all of the following are defined as characteristics of trustworthy Al EXCEPT?
- A. Explainable and Interpretable.
- B. Accountable and Transparent.
- C. Secure and Resilient.
- D. Tested and Effective.
Antwort: A
Begründung:
The NIST AI Risk Management Framework outlines several characteristics of trustworthy AI, including being secure and resilient, explainable and interpretable, and accountable and transparent. While being tested and effective is important, it is not explicitly listed as a characteristic of trustworthy AI in the NIST framework.
The focus is more on the system's ability to function safely, securely, and transparently in a way that stakeholders can understand and trust. Reference: AIGP Body of Knowledge, NIST AI RMF section.
56. Frage
What is the most important reason to document the results of AI testing?
- A. To support post-deployment maintenance.
- B. To create a verifiable audit trail.
- C. To identify areas for red-teaming focus.
- D. To limit the need for future testing cycles.
Antwort: B
Begründung:
Testing results need to bedocumented thoroughlyto ensuretraceability, accountability, and compliance. This is central to enabling audits, investigations, or regulatory inquiries into the system's development and performance.
From theAI Governance in Practice Report2025:
"Documentation and recordkeeping are essential components... to demonstrate AI system compliance, trace system behavior, and support audits and conformity assessments." (p. 34-35)
"Maintaining audit trails across development and deployment enables transparency and accountability." (p.
12)
* AandBare benefits, but not theprimary governance justification.
* D- Limiting future testing is not a recommended goal.
57. Frage
What is the most important factor when deciding whether or not to select a proprietary AI model?
- A. How frequently it will be updated.
- B. What business purpose it will serve.
- C. Whether its system card identifies risks.
- D. Whether its training data is disclosed.
Antwort: B
Begründung:
Theprimary considerationin selecting any AI system, especially aproprietary model, is itsfit for business purpose. Whether it serves the intended goals is foundational before evaluating technical or governance features.
From theAI Governance in Practice Report 2024:
"AI governance starts with defining the corporate strategy for AI... and aligning systems with business purpose and operational context." (p. 11)
* B, C, Dare relevant for evaluation, but onlyafterconfirming business applicability.
58. Frage
......
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