IAPP AIGP Web-based Practice Exam

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IAPP AIGP Exam Syllabus Topics:

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

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q136-Q141):

NEW QUESTION # 136
According to the EU AI Act, which of the following non-compliance examples could lead to fines of up to €15 million or three percent of their annual total worldwide turnover in the preceding financial year (whichever is higher)?

A. In case of AI Act prohibitions.
B. In case of a breach of AI Act prohibition by the Union institutions, bodies, offices and agencies.
C. In case of breach of a provider's obligations for high risk AI systems.
D. In case of the supply of misleading information to notified bodies in reply to a request.

Answer: C

Explanation:
The EU AI Act sets the €15 million / 3% of global turnover penalty tier for breaches of provider obligations for high-risk AI systems, such as failing to implement required risk management, data governance, monitoring, or documentation controls.

NEW QUESTION # 137
According to the GDPR, what is an effective control to prevent a determination based solely on automated decision-making?

A. Provide a just-in-time notice about the automated decision-making logic.
B. Define suitable measures to safeguard personal data.
C. Provide a right to review automated decision.
D. Establish a human-in-the-loop procedure.

Answer: D

Explanation:
The GDPR requires that individuals have the right to not be subject to decisions based solely on automated processing, including profiling, unless specific exceptions apply. One effective control is to establish a human-in-the-loop procedure (D), ensuring human oversight and the ability to contest decisions. This goes beyond just-in-time notices (A), data safeguarding (B), or review rights (C), providing a more robust mechanism to protect individuals' rights.

NEW QUESTION # 138
Testing data is defined as a subset of data that is used to:

A. Evaluate a model's handling of randomized edge cases.
B. Enable a model to discover and learn patterns.
C. Provide a robust evaluation of a final model.
D. Asses a model's on-going performance in production.

Answer: C

Explanation:
Testing data is used to provide an unbiased evaluation of the final model's performance before deployment.

NEW QUESTION # 139
What is the key feature of Graphical Processing Units (GPUs) that makes them well-suited to running AI applications?

A. GPUs can access memory quickly, resulting in lower latency than CPUs.
B. The number of transistors on GPUs doubles every two years, making the chips smaller and lighter.
C. GPUs can run every task on a computer, making them more robust than CPUs.
D. GPUs run many tasks concurrently, resulting in faster processing.

Answer: D

Explanation:
GPUs excel at parallel processing, enabling them to run many tasks concurrently, which speeds up AI computations significantly compared to CPUs.

NEW QUESTION # 140
Under the Canadian Artificial Intelligence and Data Act, when must the Minister of Innovation, Science and Industry be notified about a high-impact AI system?

A. When the algorithmic impact assessment has been completed.
B. Upon release of a new version of the system.
C. When use of the system causes or is likely to cause material harm.
D. Upon initial deployment of the system.

Answer: C

Explanation:
Under the Canadian Artificial Intelligence and Data Act (AIDA), the responsible party must notify the Minister of Innovation, Science and Industry as soon as feasible if the use of a high-impact AI system results in or is likely to result in material harm.

NEW QUESTION # 141
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