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Valid IAPP AIGP Test Papers & AIGP New Dumps Free

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IAPP AIGP Exam Syllabus Topics:

Topic
Details

Topic 1

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 2

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.

Topic 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.

Topic 4

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.

IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q126-Q131):

NEW QUESTION # 126
What is the primary purpose of an AI impact assessment?

A. To determine whether a conformity assessment is needed
B. To identify and measure the benefits of an AI system
C. To anticipate and manage the potential risks and harms of an AI system
D. To escalate the findings to the appropriate owner(s)

Answer: C

Explanation:
The correct answer is D. AI Impact Assessments are primarily used to identify and manage risks and harms associated with AI systems.
From the AIGP Body of Knowledge:
"The goal of an AI impact assessment is to ensure that risks are identified, evaluated, and mitigated prior to or during development and deployment." As further confirmed in the AI Governance in Practice Report 2024 (Part III):
"Risk-based tools like DPIAs and Algorithmic Impact Assessments help identify potential risks to individuals and society, enabling organizations to implement mitigation plans and safeguards." While benefits may be noted in such assessments, the core objective is to manage risks and promote responsible AI.

NEW QUESTION # 127
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 other stakeholder groups should be involved in the selection and implementation of the Al hiring tool?

A. Supply Chain and Marketing.
B. Litigation and Product Development.
C. Finance and Legal.
D. Marketing and Compliance.

Answer: C

Explanation:
In the selection and implementation of the AI hiring tool, involving Finance and Legal is crucial. The Finance team is essential for assessing cost implications, budget considerations, and financial risks. The Legal team is necessary to ensure compliance with applicable laws and regulations, including those related to data privacy, employment, and anti-discrimination. Involving these stakeholders ensures a comprehensive evaluation of both the financial viability and legal compliance of the AI tool, mitigating potential risks and aligning with organizational objectives and regulatory requirements.

NEW QUESTION # 128
A US hospital plans to develop an AI that will review available patient data in order to propose an initial diagnosis to licensed physicians. The hospital will implement a policy that requires physicians to consider the AI proposal, but conduct their own physical examinations prior to making a final diagnosis.
An important ethical concern with this plan is?

A. Whether patients will receive an economic benefit from the use of AI.
B. Whether the AI was trained on a representative dataset.
C. Whether the AI will have an error rate comparable to human physicians.
D. Whether physicians understand how the AI works.

Answer: B

Explanation:
The core ethical concern when deploying diagnostic AI in a healthcare setting is ensuringfairness and accuracy across diverse patient populations. If the AI is trained on a dataset that isnot representativeof the population it will serve, it risks reinforcing health disparities and leading to misdiagnoses.
From theAI Governance in Practice Report 2024:
"Training datasets lacking in diversity can produce outputs that systematically underperform for certain groups... this can lead to inaccurate or biased outcomes in healthcare settings." (p. 41)
"Bias, discrimination and fairness challenge... inadequate or nonrepresentative training data can result in AI systems that propagate historical disparities." (p. 42) While physician oversight may reduce risk,biased data can still shape clinical decision-making.
* A- Economic benefit is not central to ethical risk here.
* C- Important but less critical than data representativeness.
* D- Error rate matters but is addressed via validation; it's not the core ethical issue.

NEW QUESTION # 129
Pursuant to the White House Executive Order of November 2023, who is responsible for creating guidelines to conduct red-teaming tests of Al systems?

A. Office of Science and Technology Policy (OSTP).
B. National Institute of Standards and Technology (NIST).
C. National Science and Technology Council (NSTC).
D. Department of Homeland Security (DHS).

Answer: B

Explanation:
The White House Executive Order of November 2023 designates the National Institute of Standards and Technology (NIST) as the responsible body for creating guidelines to conduct red-teaming tests of AI systems.
NIST is tasked with developing and providing standards and frameworks to ensure the security, reliability, and ethical deployment of AI systems, including conducting rigorous red-teaming exercises to identify vulnerabilities and assess risks in AI systems.
Reference: AIGP BODY OF KNOWLEDGE, sections on AI governance and regulatory frameworks, and the White House Executive Order of November 2023.

NEW QUESTION # 130
An Al system that maintains its level of performance within defined acceptable limits despite real world or adversarial conditions would be described as?

A. Reinforced.
B. Robust.
C. Reliable.
D. Resilient.

Answer: D

Explanation:
An AI system that maintains its level of performance within defined acceptable limits despite real-world or adversarial conditions is described as resilient. Resilience in AI refers to the system's ability to withstand and recover from unexpected challenges, such as cyber-attacks, hardware failures, or unusual input data. This characteristic ensures that the AI system can continue to function effectively and reliably in various conditions, maintaining performance and integrity. Robustness, on the other hand, focuses on the system's strength against errors, while reliability ensures consistent performance over time. Resilience combines these aspects with the capacity to adapt and recover.

NEW QUESTION # 131
......

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