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PECB ISO/IEC 42001:2023 Artificial Intelligence Management System Lead Auditor ISO-IEC-42001-Lead-Auditor Dumps in PDF

Free PECB ISO-IEC-42001-Lead-Auditor Real Questions (page: 3)

ISO-IEC-42001-Lead-Auditor PDF — 120 Questions

[Fundamental Principles and Concepts of an AI Management System] Which among the following is NOT a level of AI?

  1. Artificial Narrow Intelligence
  2. Artificial Machine Intelligence
  3. Artificial General Intelligence
  4. Artificial Super Intelligence

Answer(s): B



[Fundamental Principles and Concepts of an AI Management System] Which among the following is NOT a core element of AIMS?

  1. Independence and honesty
  2. Fairness and non-discrimination
  3. Privacy and security
  4. Safety and reliability

Answer(s): A



[Fundamental Audit Concepts and Principles]
Audit evidence must be:

  1. Verifiable
  2. Physical
  3. Refutable
  4. Structured

Answer(s): A



[AI Management System Requirements]
The process to assess the potential consequences for individuals or groups of individuals, or both, and societies that can result from the AI system throughout its life cycle is known as:

  1. AI System Risk Assessment
  2. AI System Impact Assessment
  3. Documentation of AI Systems
  4. None of the above

Answer(s): B



[Fundamental Audit Concepts and Principles]
What type of evidence is an external audit report?

  1. Physical
  2. Confirmative
  3. Analytical
  4. Technical

Answer(s): B



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A
AI Tutor Explanation
8/3/2026 4:40:02 AM

Question 2:
For Question 2, the correct concept is C) Machine Learning (ML).

  • Reason: Predicting future buying behavior from browsing history and past purchases is a predictive analytics task best handled by ML, which learns patterns from historical data.
  • Why not NLP or Computer Vision: NLP is for text data; Computer Vision is for images/videos; neither directly fits predicting customer behavior from structured user data.
  • About Deep Learning: DL is a subset of ML, useful for very large or unstructured data; but for typical retail prediction with structured data, general ML approaches are more appropriate and interpretable.

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