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Authoritative Practice AIGP Exam Online & Leader in Qualification Exams & Newest IAPP IAPP Certified Artificial Intelligence Governance Professional

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IAPP AIGP Exam Syllabus Topics:

Topic
Details

Topic 1

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 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 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.

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q72-Q77):

NEW QUESTION # 72
Which of the following is a subcategory of Al and machine learning that uses labeled datasets to train algorithms?

A. Segmentation.
B. Generative Al.
C. Expert systems.
D. Supervised learning.

Answer: D

Explanation:
Supervised learning is a subcategory of AI and machine learning where labeled datasets are used to train algorithms. This process involves feeding the algorithm a dataset where the input-output pairs are known, allowing the algorithm to learn and make predictions or decisions based on new, unseen data. Reference:
AIGP BODY OF KNOWLEDGE, which describes supervised learning as a model trained on labeled data (e.g., text recognition, detecting spam in emails).

NEW QUESTION # 73
Scenario:
Business A provides grammar and writing assistance tools and licenses a generative AI model from Business B to enhance its offerings. Business A is concerned that the AI model might produce inappropriate or toxic content and wants to implement governance processes to prevent this.
Which of the following governance processes should Business A take to best protect its users against potentially inappropriate text?

A. Business A should establish a user reporting feature that allows users to flag toxic or obscene text, and report any incidents to Business B
B. Business A should test that the AI model performs as expected and meets their minimum requirements for filtering toxic or obscene text
C. Business A should ask Business B for detailed documentation on the generative AI model's training data and whether it contained toxic or obscene sources
D. Business A should fine-tune the AI model on user-generated text that has been verified to be appropriate

Answer: B

Explanation:
The correct answer is B. According to responsible AI practices, pre-deployment testing to ensure the model behaves as expected and aligns with organizational requirements is critical.
From the AIGP ILT Guide:
"Testing for unacceptable outcomes such as toxicity, discrimination, or hallucinations should be included in the AI governance life cycle, particularly during development and prior to deployment." Also emphasized in the AI Governance in Practice Report 2024:
"Organizations must verify legal and regulatory compliance, monitor performance, and mitigate risks prior to deployment." Testing the model to meet safety and appropriateness standards is more proactive and preventive than relying solely on user reporting or requesting documentation.

NEW QUESTION # 74
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.
If XYZ does not deploy and use the Al hiring tool responsibly in the United States, its liability would likely increase under all of the following laws EXCEPT?

A. Privacy laws.
B. Accessibility laws.
C. Product liability laws.
D. Anti-discriminationlaws.

Answer: C

Explanation:
In the United States, the use of AI hiring tools must comply with anti-discrimination laws, accessibility laws, and privacy laws to avoid increasing liability. Anti-discrimination laws (A) ensure that hiring practices do not unlawfully discriminate against protected classes. Accessibility laws (C) require that hiring tools are accessible to all applicants, including those with disabilities. Privacy laws (D) govern the handling of personal data during the hiring process. Product liability laws (B), however, typically apply to the safety and reliability of physical products and would not generally increase liability specifically related to the responsible use of AI hiring tools in the employment context.

NEW QUESTION # 75
According to the EU Al Act, providers of what kind of machine learning systems will be required to register with an EU oversight agency before placing their systems in the EU market?

A. Al systems that are harmful based on a legal risk-utility calculation.
B. Al systems trained on sensitive personal data.
C. Al systems that are high-risk.
D. Al systems that are "strong" general intelligence.

Answer: C

Explanation:
According to the EU AI Act, providers of high-risk AI systems are required to register with an EU oversight agency before these systems can be placed on the market. This requirement is part of the Act's framework to ensure that high-risk AI systems comply with stringent safety, transparency, and accountability standards.
High-risk systems are those that pose significant risks to health, safety, or fundamental rights. Registration with oversight agencies helps facilitate ongoing monitoring and enforcement of compliance with the Act's provisions. Systems categorized under other criteria, such as those trained on sensitive personal data or exhibiting "strong" general intelligence, also fall under scrutiny but are primarily covered under different regulatory requirements or classifications.

NEW QUESTION # 76
Training data is best defined as a subset of data that is used to?

A. Enable a model to detect and learn patterns.
B. Fine-tune a model to improve accuracy and prevent overfitting.
C. Resemble the structure and statistical properties of production data.
D. Detect the initial sources of biases to mitigate prior to deployment.

Answer: A

Explanation:
Training data is used to enable a model to detect and learn patterns. During the training phase, the model learns from the labeled data, identifying patterns and relationships that it will later use to make predictions on new, unseen data. This process is fundamental in building an AI model's capability to perform tasks accurately. Reference: AIGP Body of Knowledge on Model Training and Pattern Recognition.

NEW QUESTION # 77
......

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Jack Moore Jack Moore

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