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Learning the fundamentals of AI ethics and ISO/IEC 42001 (AIMS)
Your AI projects need governance and discussion that goes beyond performance alone. Understand ethical challenges and the ISO/IEC 42001 framework to clarify responsibilities and areas requiring attention. Develop a foundation for contributing to a structured AI management approach.
- Duration
- 2 days 14 hours
- Code
- IA031FR Code
Presentation
The growth of artificial intelligence confronts businesses with unprecedented ethical and regulatory challenges, reinforced by the arrival of the European AI Act. Sustainable innovation requires governance capable of anticipating bias, discrimination and non-compliance risks. This 2-day course provides the keys to combining technological performance with social responsibility.
The programme offers a dual approach: immersion in fundamental algorithmic ethics principles and practical introduction to the ISO/IEC 42001:2023 standard. Through workshops and case studies, you will learn to map risks, define an ethics charter and understand the structure of an Artificial Intelligence Management System (AIMS) adapted to your organisation.
By the end of the session, you will have a practical methodology for placing ethics at the heart of AI projects. You will be able to contribute to system compliance and establish a culture of digital trust that meets regulator and end-user expectations.
Objectives
By the end of this course, you will be able to:
- Analyse ethical, societal and legal impacts associated with deploying AI solutions;
- identify the guiding principles and structure of ISO/IEC 42001;
- describe the requirements of an Artificial Intelligence Management System (AIMS) to ensure compliance;
- integrate ethical control mechanisms into project management and business processes;
- define an AI governance policy aligned with organisational values and strategy.
Program
Module 1: Understanding and applying AI ethics
- Key concepts and universal AI principles: transparency, fairness and explainability.
- Identifying major risks: cognitive bias, discrimination and surveillance misuse.
Practical exercises
- Conduct an ethical analysis of a concrete use case in recruitment, healthcare or scoring.
Module 2: Navigating the regulatory landscape
- The relationship between the GDPR, the European AI Act and international standards from UNESCO and the OECD.
Practical exercises
- Map applicable regulatory obligations according to AI system type.
Module 3: Putting ethics into practice in projects
- Structuring ethical governance: defining roles and responsibilities.
- Deploying control tools: audit grids, checklists and validation procedures.
Practical exercises
- Draft an AI ethics charter suited to an organisation's context.
Module 4: Understanding ISO/IEC 42001
- Introduction to ISO 42001:2023 architecture, terminology and objectives.
- Comparative analysis with other management standards (ISO 27001:2022 and ISO 9001:2015).
- Validating key concepts through interactive exercises.
Practical exercises
- Validate understanding of the standard's key concepts through an interactive quiz.
Module 5: Implementing an Artificial Intelligence Management System (AIMS)
- Defining AI policy, leadership and planning processes.
- Developing an AI-specific risk assessment methodology.
- Implementing operational controls and continuous improvement cycles.
Practical exercises
- Simulate a complete AIMS deployment in a fictional organisation.
Audience
This course is intended for innovation and compliance stakeholders, including:
- AI project managers and Product Owners responsible for their solutions' ethical viability;
- Compliance and quality managers structuring the company's standards framework;
- Data scientists and data engineers seeking to integrate responsibility requirements into models;
- Digital transformation leaders managing AI adoption strategy;
- Any stakeholder involved in data governance.
Prerequisites
This course requires the following prerequisites:
- Professional experience: familiarity with project management, quality or compliance is recommended to understand governance challenges.
- Basic knowledge:
- General awareness of AI and its use cases;
- awareness of CSR or regulatory issues.
Teaching and assessment methods
- Initial skills assessment
- Training materials provided to participants
- Continuous assessment throughout the course
- End-of-course feedback questionnaire
- Combination of theory and practical application
- Attendance records
- Post-course follow-up evaluation
- Quiz / multiple-choice questions
- Practical exercises
Course highlights
- Dual expertise: develop a distinctive combination of strategic ethical insight and technical command of ISO 42001:2023.
- Operational grounding: turn theoretical concepts into practical governance tools through 5 directly applicable workshops.
- Anticipating compliance: prepare confidently for future regulatory requirements, particularly those imposed by the European AI Act.
- AIMS methodology: acquire international standards to structure and sustain AI management.
Dates and sessions
Choose the date and delivery format that suit you.
No upcoming sessions are currently available.