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ISO-IEC-42001-Lead-Auditor Exam Dumps - ISO/IEC 42001:2023 Artificial Intelligence Management System Lead Auditor Exam

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Question # 17

A social media platform wants to automatically detect and remove inappropriate content from images and videos uploaded by users. Which AI concept is most appropriate for this task?

A.

Natural Language Processing (NLP)

B.

Computer Vision

C.

Machine Learning (ML)

D.

Deep Learning (DL)

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Question # 18

Question:

During a combined audit, if an auditor identifies a finding linked to one criterion, should they consider its potential impact on corresponding or related criteria of other management systems?

A.

Yes, the auditor should consider the other criteria only if the finding is deemed significant

B.

Yes, the auditor should consider the possible impact on the corresponding or similar criteria of the other management system

C.

No, in such cases the auditor should always focus on the specific criterion identified

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Question # 19

During the audit planning phase, what is the primary activity an auditor should focus on?

A.

Conducting interviews with staff

B.

Preparing checklists and audit plans

C.

Issuing corrective actions

D.

Reviewing the final report

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Question # 20

Question:

While preparing for an AIMS audit, a technology company faced an issue: the auditor lacked a required security clearance for accessing sensitive information related to government contracts.

The company requested a replacement auditor. Is this acceptable?

A.

Yes, the auditor not holding the security clearance required by the auditee is a valid reason to request the replacement of the auditor

B.

No, the auditee can request the replacement of the auditor only if the auditor is in a conflict of interest situation

C.

No, the auditee can request the replacement of the auditor only if the auditor has audited the company in the past

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Question # 21

Which international standard does the top management of NeuraGen apply to govern the effective use of AI? (Refer to Scenario 1)

Scenario: NeuraGen, founded by a team of AI experts and data scientists, has gained attention for its advanced use of artificial intelligence. It specializes in developing personalized learning platforms powered by AI algorithms. MindMeld, its innovative product, is an educational platform that uses machine learning and stands out by learning from both labeled and unlabeled data during its training process. This approach allows MindMeld to use a wide range of educational content and personalize learning experiences with exceptional accuracy. Furthermore, MindMeld employs an advanced AI system capable of handling a wide variety of tasks, consistently delivering a satisfactory level of performance. This approach improves the effectiveness of educational materials and adapts to different learners' needs.

NeuraGen skillfully handles data management and AI system development, particularly for MindMeld. Initially, NeuraGen sources data from a diverse array of origins, examining patterns, relationships, trends, and anomalies. This data is then refined and formatted for compatibility with MindMeld, ensuring that any irrelevant or extraneous information is systematically eliminated. Following this, values are adjusted to a unified scale to facilitate mathematical comparability. A crucial step in this process is the rigorous removal of all personally identifiable information (PII) to protect individual privacy. Finally, the data is subjected to quality checks to assess its completeness, identify any potential bias, and evaluate other factors that could impact the platform's efficacy and reliability.

NeuraGen has implemented an advanced artificial intelligence management system (AIMS) based on ISO/IEC 42001 to support its efforts in AI-driven education. This system provides a framework for managing the life cycle of AI projects, ensuring that development and deployment are guided by ethical standards and best practices.

NeuraGen's top management is key to running the AIMS effectively. Applying an international standard that specifically provides guidance for the highest level of company leadership on governing the effective use of AI, they embed ethical principles such as fairness, transparency, and accountability directly into their strategic operations and decision-making processes.

While the company excels in ensuring fairness, transparency, reliability, safety, and privacy in its AI applications, actively preventing bias, fostering a clear understanding of AI decisions, guaranteeing system dependability, and protecting user data, it struggles to clearly define who is responsible for the development, deployment, and outcomes of its AI systems. Consequently, it becomes difficult to determine responsibility when issues arise, which undermines trust and accountability, both critical for the integrity and success of AI initiatives.

A.

ISO/IEC 38507

B.

ISO/IEC 22989

C.

ISO/IEC 23503

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Question # 22

A global bank is currently evaluating the effectiveness of its AI management system controls through an AIMS audit. Which role is being played by this company?

A.

An accreditation body

B.

A certification body

C.

An auditee

D.

An advisory body

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Question # 23

Was the arrangement for assigning guides during the audit process appropriate?

A.

Yes, the arrangement was appropriate

B.

No, because every auditor must have a guide accompanying them

C.

No, because the auditee should not influence the guide selection process

D.

No, because guides must be independent of the auditee

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Question # 24

During a certification audit, the audit team reviewed the defined roles and responsibilities within the auditee and conducted interviews with key personnel. They also evaluated whether the roles and responsibilities were aligned with the AI policy and objectives, examined reporting mechanisms for concerns, and reviewed the reporting frequency and response time for AI-related matters. The implementation of which control of ISO/IEC 42001 is being verified in this case?

A.

A.3 Internal organization

B.

A.4 Resources for AI systems

C.

A.5 Assessing impacts of AI systems

D.

A.6 External context and stakeholder engagement

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