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Pass Guaranteed IAPP - AIGP - High Hit-Rate Test IAPP Certified Artificial Intelligence Governance Professional Cram

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IAPP AIGP Exam Syllabus Topics:

Topic
Details

Topic 1

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 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 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 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.

IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q87-Q92):

NEW QUESTION # 87
Scenario:
A financial services company is planning a new AI project to assess creditworthiness. The AI team is mapping out what tasks should be completed during the planning phase of the AI lifecycle.
The planning phase of the AI lifecycle includes all of the following EXCEPT:

A. Definition of underlying assumptions
B. Approach to governance
C. Context in which the model will operate
D. Choice of the architecture

Answer: D

Explanation:
The correct answer is C. The choice of architecture (e.g., neural networks vs. decision trees) is typically part of the design and development phase, not the initial planning.
From the AIGP Body of Knowledge - AI Lifecycle Module:
"Planning involves scoping, context definition, stakeholder identification, governance planning, and assumptions-not yet model selection." Confirmed in the ILT Participant Guide:
"Design decisions such as architecture or algorithm type come after planning-usually during development based on technical feasibility and data availability."

NEW QUESTION # 88
Which of the following may be permissible uses of an AI system under the EU AI Act EXCEPT?

A. Using biometrics in abduction cases
B. Detecting emotions in a telemedicine session
C. Detecting emotions in a workplace for employee morale
D. Improving the response time for emergency services

Answer: C

Explanation:
The correct answer is D. Emotion recognition in the workplace is flagged as unacceptable or highly restricted under the EU AI Act due to its intrusive nature and potential for misuse.
From the AIGP ILT Guide - EU AI Act Training Module:
"AI systems that monitor individuals' emotions in the workplace or educational settings are listed among prohibited or strictly limited practices under Article 5." AI Governance in Practice Report 2024 supports this interpretation:
"Emotion recognition systems, especially in sensitive contexts such as employment or education, raise significant concerns under EU fundamental rights law and are likely to be restricted." Other uses listed-such as emergency response or emotion detection in healthcare-may fall under lawful and beneficial uses, especially when justified by public interest.

NEW QUESTION # 89
Retraining an LLM can be necessary for all of the following reasons EXCEPT?

A. Adjust the model's hyper parameters to a specific use case.
B. To ensure interpretability of the model's predictions.
C. To minimize degradation in prediction accuracy due tochanges in data.
D. Account for new interpretations of the same data.

Answer: B

Explanation:
Retraining an LLM (Large Language Model) is primarily done to improve or maintain its performance as data changes over time, to fine-tune it for specific use cases, and to incorporate new data interpretations to enhance accuracy and relevance. However, ensuring interpretability of the model's predictions is not typically a reason for retraining. Interpretability relates to how easily the outputs of the model can be understood and explained, which is generally addressed through different techniques or methods rather than through the retraining process itself. References to this can be found in the IAPP AIGP Body of Knowledge discussing model retraining and interpretability as separate concepts.

NEW QUESTION # 90
A US company has developed an Al system, CrimeBuster 9619, that collects information about incarcerated individuals to help parole boards predict whether someone is likely to commit another crime if released from prison.
When considering expanding to the EU market, this type of technology would?

A. Require the company to register the tool with the EU database.
B. Require a detailed conformity assessment.
C. Be subject approval by the relevant EU authority.
D. Be banned under the EU Al Act.

Answer: D

Explanation:
Under the EU AI Act, high-risk AI systems like CrimeBuster 9619 would require a detailed conformity assessment before being deployed in the EU market. This assessment ensures that the AI system complies with all relevant regulations and standards, addressing potential risks related to privacy, security, and discrimination. The company would not need to register the tool with the EU database (A), seek approval from an EU authority (B), or face a ban (D) as long as it meets the necessary conformity requirements.

NEW QUESTION # 91
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.
The frameworks that would be most appropriate for XYZ's governance needs would be the NIST Al Risk Management Framework and?

A. Human Rights, Democracy, and Rule of Law Impact Assessment (HUDERIA).
B. IEEE Ethical System Design Risk Management Framework (IEEE 7000-21).
C. NIST Information Security Risk (NIST SP 800-39).
D. NIST Cyber Security Risk Management Framework (CSF 2.0).

Answer: B

Explanation:
The IEEE Ethical System Design Risk Management Framework (IEEE 7000-21) would be most appropriate for XYZ Corp's governance needs in addition to the NIST AI Risk Management Framework. The IEEE framework specifically addresses ethical concerns during system design, which is crucial for ensuring the responsible use of AI in hiring. It complements the NIST framework by focusing on ethical risk management, aligning well with XYZ Corp's goals of deploying AI responsibly and mitigating associated risks.

NEW QUESTION # 92
......

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