The standard: ISO/IEC 42001:2023 Information technology Artificial intelligence Management system - Requirements

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This course is an integrated course, with dual advantage - Lead Implementer and Lead Auditor - based on the philosophy that an implementer and an auditor should be knowledgeable on auditing and implementation requirements and nuances. The gap in their understandings lead to ineffectiveness of implementation and/or auditing.

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ISO/IEC 42001 is an international standard that specifies requirements for establishing, implementing, maintaining, and continually improving an Artificial Intelligence Management System (AIMS) within organizations. It is designed for entities providing or utilizing AI-based products or services, ensuring responsible development and use of AI systems.

 

ISO/IEC 42001 is the world’s first AI management system standard, providing valuable guidance for this rapidly changing field of technology. It addresses the unique challenges AI poses, such as ethical considerations, transparency, and continuous learning. For organizations, it sets out a structured way to manage risks and opportunities associated with AI, balancing innovation with governance.

 

In this intensive course, participants develop the competence to master a model for implementing artificial intelligence risk management processes throughout their organization using the ISO/IEC 42001:2023 standard as a reference framework. Based on practical exercises and discussions, participants acquire the necessary knowledge on the practical application of the standard and learn how to meet the requirements specified in the standard. The delegates will develop skills to audit an AIMS based on ISO/IEC 42006 (currently in DIS stage) standard.

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Topics coverage

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Lead Implementer

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• What is Artificial Intelligence (AI)?

• What is Machine Learning (ML)?

• The concept of data science 

• AI concepts and terminologies

• How AI becomes disruptive

• AI considerations

• Regulatory stipulations

• Transparency needs

• What is ISO/IEC 42001:2023 standard?

  • Applicability of the standard 

  • Benefits 

  • Responsible use of AI

  • Efficiency factors

  • Risk based approach

  • Traceability, transparency and reliability

  • Clauses and requirements​

• ISO 22989:2022 standard 

• ISO/IEC 23053:2022 standard - Framework for Artificial Intelligence (AI)  Systems Using Machine Learning (ML)

• ISO/IEC 23894:2023 standard - Artificial intelligence - Guidance on risk management

• ISO/IEC 42001:2023 Implementation steps

• Case studies and exercises

 

Lead Auditor - additional topics​

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• Introduction to ISO/IEC 42006:2024 (Currently in DIS stage)

• Auditing principles

• Conflict of interest

• Structural requirements

• Resource requirements for conducting AI audits

  • For application review

  • For audit report review

  • For making certification decisions

  • For making decisions on appeals

• Information requirements​

  • AIMS certification documents​

• Process requirements

  • Audit program​me

  • Audit methodology

  • Audit time

  • Sampling

  • Combined audit

• Audit planning

  • Audit objectives​

  • Audit criteria

  • Audit plan for AIMS

• initial certification​

  • Stage 1 audit​

  • Stage 2 audit

• Conducting audits​

  • Specific elements of AIMS audits​

  • Audit reporting

• Certification maintenance

• Surveillance audits

• Recertification audits

• Special audits

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What you will learn?

After completing this course you will be able to 

• Understand the basics of AI and ML

• Understand the framework and apply the standard for managing risk and opportunities 

• Demonstrate responsible use of AI

• Establish traceability, transparency and reliability 

• Enable cost savings and efficiency gains

• What is involved in AIMS audits

• How to perform effective audits to ensure a robust AIMS is in place and functioning well

 

 The case studies and the exercises will help a learner get a grip on the subject. 

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​Who should attend?

• Management system auditors

• Risk managers (ERM or Infosec/AI RM)

• Executive level stakeholders – CEO, CFO, HR Head, CTO, CIO

• Business Process Owners

• Business Finance Managers

• Business Risk Managers

• Regulatory Compliance Managers

• Business Function Managers

• AI Developers, AI Operators 

• Quality Managers 

• Business Excellence Professionals 

• Information Security Professionals 

• Consultants 

• AI Service Vendors 

• AI process practitioners

• AI Project Managers

• AI architects

• Information security managers

• Any AI Stakeholder, in any manner Management System Auditors

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Delivery approach:

​This training is based  on both theory and practice:

• Sessions of lectures illustrated with examples

• Practical exercises based on various scenarios

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What you get?

• Course material access - e-version

• Training session delivered by an eminent instructor 

• Certification examination

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Course delivered online as instructor led live virtual course or class room session. Delivered across the globe. 

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Course duration?

• Lead Implementer: 4 days

• Lead Auditor: 5 days

• Integrated course: 5 days

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​Prerequisite:

• Nil

• Desired: an understanding of the data analysis techniques and data science concepts

 

Examination (each exam)

• Multiple Choice, 50 Questions

• Exam duration: 90 Minutes

• Exam mode: Paper based or online remotely proctored. 

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Contact for further details. See the schedule here.

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• © ISO/IEC 42001:2023 and all other ISO(/IEC) standards - Copyright ownership is with International Organisation for Standardisation and International Electrotechnical Commission as appropriate

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