PECB ISO-IEC-42001-Lead-Auditor Exam With Confidence Using Practice Dumps

The principle of Fairness and Non-Discrimination is one of the core ethical and governance pillars emphasized in ISO/IEC 42001:2023, especially in Clause 4.2 (Understanding the needs and expectations of interested parties) and Clause 6.1 (Actions to address risks and opportunities) where ethical risks related to AI systems are assessed.

According to the standard and accompanying PECB training guide, fairness is defined as ensuring that AI systems do not create or perpetuate bias, and that individuals and groups are treated equitably, with measures in place to detect and mitigate discrimination. This is often embedded in risk assessments and operational controls when managing AI systems.

In ISO/IEC 42001, organizations are required to consider ethical, legal, and societal impacts of their AI systems, and Fairness and Non-Discrimination is a key tenet of trustworthy AI.

Sarah cannot audit because auditors who have contributed to the design, implementation, or maintenance of a management system must not audit that same system to avoid conflict of interest.

ISO/IEC 17021-1:2015 Clause 5.2.5 clearly states: “Personnel who have provided management system consultancy, including those acting in a managerial capacity, shall not be used to conduct audits.”

The Lead Auditor Guide explains: “Maintaining impartiality requires that individuals with consultancy roles be excluded from auditing the systems they helped create.”

The levels of AI commonly referenced in both ISO/IEC 42001 guidance materials and AI governance literature include:

Artificial Narrow Intelligence (ANI) – Specialized in a single task

Artificial General Intelligence (AGI) – Human-level general problem-solving capability

Artificial Super Intelligence (ASI) – Hypothetical AI surpassing human intelligence

Artificial Machine Intelligence is not a formally recognized level and does not appear in ISO/IEC 42001, nor in PECB’s standard AI terminology.

The PECB Lead Auditor Guide defines the recognized levels under AI system classification and clarifies that terms like "Artificial Machine Intelligence" are non-standard or colloquial and not part of professional auditing or ISO frameworks.