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GAICC ISO-IEC-42001-Foundation Exam Syllabus Topics:

Section	Weight	Objectives
Responsible AI, Ethics, and Stakeholder Awareness	20%	- Ethical principles and AI responsibility 1. Stakeholder engagement and transparency 2. Fairness, explainability and oversight mechanisms 3. Roles and responsibilities of AI providers, producers and customers
Fundamentals of AI Governance and the ISO/IEC 42001 Framework	40%	- Basic concepts of AI and AI Management Systems (AIMS) 1. Purpose, scope and structure of ISO/IEC 42001:2023 2. Terminology from ISO/IEC 22989 and ISO/IEC 42001 3. AI system lifecycle concepts - Relationship between AIMS and organizational context
Core Components of the Artificial Intelligence Management System (AIMS)	40%	- Key clauses and requirements of ISO/IEC 42001 1. Operation, performance evaluation and improvement 2. Leadership, planning and support

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GAICC ISO/IEC 42001 Foundation Sample Questions (Q39-Q44):

NEW QUESTION # 39
A foundation case study describes a media company rolling out a generative-AI content-assistance tool. Four roles are listed: the chief executive, the head of editorial standards, an AI product manager, and the legal counsel. The workshop asks who should be assigned the responsibility for reporting AIMS performance to top management under ISO/IEC 42001. Which assignment is MOST consistent with Clause 5.3 ' s intent on roles, responsibilities, and authorities?

A. Assign the reporting role to the external certification body during the audit cycle, since the certification body conducts independent verification of the AIMS and is therefore better placed than any internal role to report on AIMS performance for the period under review.
B. Assign the role to the chief executive personally, so that reporting on AIMS performance is delivered by the same person who chairs management review, on the basis that combining the two activities tightens accountability at the top of the organisation.
C. Assign the reporting role to a specific named role inside the organisation with appropriate authority over the AIMS, such as the head of editorial standards or the AI product manager, and communicate that assignment so the reporting line is unambiguous.
D. Avoid assigning the reporting role to any single named individual, on the grounds that distributed accountability across the four listed roles strengthens internal checks and balances around AIMS performance reporting to top management.

Answer: C

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
Under ISO/IEC 42001 Clause 5.3 (Organizational roles, responsibilities and authorities), top management must ensure that responsibilities and authorities for relevant roles are assigned and communicated throughout the organization. Crucially, top management must assign the specific responsibility and authority for ensuring the AIMS conforms to standard requirements and for reporting on the performance of the AIMS to top management. Combining the reporter and the reviewer by assigning reporting to the chief executive undermines independent reporting lines and violates standard management system segregation. Similarly, diffusing accountability across a broad committee without an explicit, designated reporting lead results in accountability gaps. The standard dictates that a clearly defined internal role with operational oversight-such as an AI Product Manager, Chief AI Ethics Officer, or Head of Standards-must be explicitly designated and communicated as holding formal reporting accountability.
Reference: ISO/IEC 42001:2023 Clause 5.3 (Organizational roles, responsibilities and authorities); GAICC Foundation Module 5 (Governance Structures & Accountability).

NEW QUESTION # 40
A compliance manager is preparing a slide for the leadership team to explain the difference between accreditation and certification in the ISO/IEC 42001 ecosystem. She wants a one-sentence working definition of an accreditation body that aligns with GAICC Foundation Module 2. Which option is the BEST fit?

A. An accreditation body is the publisher of an ISO standard, responsible for drafting the requirements text, maintaining revisions, and updating the harmonised structure terms.
B. An accreditation body is an authoritative third party that assesses and formally recognises the competence of certification bodies to audit against standards such as ISO/IEC 42001.
C. An accreditation body is the internal audit function within an organisation that reviews the AIMS against ISO/IEC 42001 before any external certification audit is conducted.
D. An accreditation body is the consulting firm engaged by an organisation to help draft its AI policy, conduct gap analyses, and prepare evidence packs for a Stage 1 audit.

Answer: B

NEW QUESTION # 41
A retail bank ' s procurement team has begun receiving requests from enterprise clients asking the bank to demonstrate how it governs the AI models used in credit decisioning. The Chief Risk Officer wants a single, internationally recognised framework that addresses AI specifically-not just general quality or information- security controls-and that can be independently certified. Which standard BEST fits this need under the GAICC Foundation view of why ISO/IEC 42001 was published?

A. ISO/IEC 27001, the information security management system standard, which fully addresses AI governance through its existing Annex A control set.
B. ISO/IEC 42001, the first international management system standard dedicated to artificial intelligence and capable of third-party certification.
C. ISO 9001, the international quality management system standard, which already covers AI quality assurance for regulated banking workloads.
D. The OECD AI Principles, which provide an internationally agreed policy framework for trustworthy AI and a basis for third-party certification.

Answer: B

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
ISO/IEC 42001 was developed jointly by ISO and IEC (through JTC 1/SC 42) to establish the world's first certifiable Artificial Intelligence Management System (AIMS) standard. While ISO 9001 addresses overarching quality processes and ISO/IEC 27001 governs information security, neither framework provides specialized, auditable criteria for unique AI risks, including model hallucinations, statistical bias, algorithmic drift, lack of explainability, data poisoning, and autonomous decision opacity. Furthermore, while the OECD AI Principles define high-level global policy benchmarks for trustworthy AI, they are non-binding policy guidance that lack formal conformity assessment specifications. ISO/IEC 42001 fills this gap by delivering an auditable, Harmonized Structure management system against which accredited conformity assessment bodies can perform independent third-party audits and issue formal organizational certification.
Reference: ISO/IEC 42001:2023 Scope; GAICC Foundation Module 1 (The Emergence & Global Role of ISO
/IEC 42001).

NEW QUESTION # 42
An insurer deploys an AI model that supports underwriter decisions on personal-lines policies. Three audiences need explanations: applicants who receive a decline, internal underwriters who supervise the model
' s outputs, and an external regulator conducting a market review. A foundation learner is asked how ISO/IEC
42001 expects explainability to be approached across these audiences. Which response BEST reflects the responsible-AI principle of explainability?

A. Provide a single technical explanation document, copied verbatim from the model-development team, to each of the three audiences, on the basis that a uniform explanation supports consistency and auditability across stakeholders interacting with the system.
B. Defer explainability entirely until a complaint or regulatory enquiry is raised, then assemble an explanation reactively for the specific case, since pre-built explanations may not address the particular query the requesting party actually puts to the insurer.
C. Tailor the explanation to each audience: plain-language reasoning for the declined applicant, feature- level rationale for the underwriter, and methodology and validation evidence for the regulator-each calibrated to its purpose.
D. Provide explanations to the regulator and the underwriters but withhold any explanation from declined applicants on commercial-sensitivity grounds, so that proprietary aspects of the underwriting approach remain protected from competitor scrutiny.

Answer: C

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
Explainability under ISO/IEC 42001 Annex B and Annex A domain A.8 is not a one-size-fits-all technical readout. The standard explicitly recognizes that different interested parties require information delivered at different levels of abstraction to make the explanation meaningful and actionable. For consumers receiving an adverse outcome (such as a declined policy), explainability requires plain-language reasoning detailing the principal factors and criteria that led to the determination, enabling individual understanding and potential recourse. For internal operators (underwriters), explainability demands feature-importance scores, localized attribution weights, and confidence thresholds to enable effective human oversight and validation. For supervisory regulators, explainability requires comprehensive mathematical methodology disclosures, architectural validation reports, data provenance verification, and fairness audit records. Calibrating explanations to stakeholder contexts reflects the core principles of transparency, accountability, and user- centric governance.
Reference: ISO/IEC 42001:2023 Annex B.5 (Transparency and explainability); Control Domain A.8 (AI system operations); GAICC Foundation Module 6 (Calibrated Explainability and Stakeholder Communication).

NEW QUESTION # 43
A travel platform plans to train a recommendation model on five years of customer booking history, including names, contact details, and trip itineraries. The data-protection officer raises concerns about training-data use.
The AI governance lead is asked how ISO/IEC 42001 treats the relationship between AI management and personal-data protection. Which response BEST reflects the standard ' s intent on privacy as a responsible-AI consideration?

A. Personal-data protection is a relevant input to the AI System Impact Assessment under Clause 6.1.4, and the AIMS should coordinate with applicable privacy obligations rather than treating data protection as a separate concern outside the scope of AI governance.
B. The AIMS should record an exception noting that training data is exempt from privacy review on grounds of model improvement, since pursuit of model accuracy provides a legitimate operational basis for the platform ' s use of historical booking information in training.
C. The AI governance lead should remove privacy considerations from the AI System Impact Assessment scope and refer them to the privacy officer for a parallel assessment, with no formal linkage between the two assessment processes maintained within the AIMS records.
D. Personal-data protection sits entirely outside the AIMS because ISO/IEC 42001 governs AI systems and applicable privacy laws govern personal data, so the two regimes operate independently with no expectation of coordination across them.

Answer: A

Explanation:
Comprehensive and Detailed Explanation From [GAICC ISO/IEC 42001/Course Guide/topics]:
ISO/IEC 42001 explicitly integrates data protection and privacy within its governance requirements. Under Clause 6.1.4 (AI system impact assessment), Clause 4.2 (Compliance obligations), and Annex A domain A.7 (Data for AI systems), privacy considerations are recognized as critical inputs to responsible AI management.
AI models trained on personal booking records present significant risks regarding data repurposing, re- identification, model inversion attacks, and non-compliance with data protection legislation (such as GDPR or regional equivalents). Rather than siloing AI governance from data privacy, the standard mandates active coordination. AI risk and impact assessments must evaluate privacy risks, enforce data minimization and pseudonymization, and document lawful processing baselines within the AIMS. Treating privacy as completely isolated from AI oversight or asserting unilateral exemptions for training activities directly violates the standard.
Reference: ISO/IEC 42001:2023 Clause 6.1.4; Control Domain A.7; Annex B.6 (Privacy); GAICC Foundation Module 7 (Data Protection, Privacy, and Model Lifecycle Governance).

NEW QUESTION # 44
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