Overview
This two-day course introduces Responsible Artificial Intelligence (RAI) as an approach to designing, developing, deploying, and using AI systems responsibly throughout their lifecycle. It is intended for professionals and decision-makers responsible for managing the ethical, organizational, regulatory, and technical risks associated with AI.
Aligned with ISO/IEC 42001:2023 and the EU AI Act, the course helps participants establish organizational AI principles, policies, objectives, risk-management practices, and AI management system processes. It also examines requirements affecting high-risk AI systems and provides a structured foundation for responsible AI governance that extends beyond safety, security, or regulatory compliance alone.
Participants apply these concepts through practical exercises and an automotive case study involving pedestrian detection in automated driving systems (ADS). Although this scenario provides continuity throughout the training, the principles and processes can be applied across industries and AI applications.
Intended Audience
This course is intended for professionals involved in developing, governing, evaluating, or overseeing AI systems. It is particularly relevant for:
- Executives and decision-makers establishing organizational AI strategies, principles, or policies
- AI governance, risk, compliance, legal, and regulatory professionals
- Systems, software, data, and machine-learning engineers developing AI-enabled products and services
- Product managers and technical leaders responsible for AI system development or deployment
- Safety, cybersecurity, privacy, quality, and assurance professionals evaluating AI-related risks
- Professionals working with high-risk AI systems or preparing for EU AI Act obligations
- Organizations implementing or evaluating an AI management system aligned with ISO/IEC 42001:2023
Objectives
By the end of this course, participants will be able to:
- Lead organizational discussions about Responsible AI and establish appropriate AI principles, objectives, and policies
- Explain the structure and purpose of an AI management system aligned with ISO/IEC 42001:2023
- Identify, assess, and treat AI-related risks using a structured risk-management approach
- Conduct an AI system impact assessment and identify appropriate AI controls
- Interpret key EU AI Act requirements affecting high-risk AI systems
- Apply Responsible AI practices throughout the AI system lifecycle
- Evaluate and improve organizational AI management processes through performance evaluation, audits, nonconformity management, and corrective action
Agenda
Below you will find an outline of the training course schedule.
DAY 1
- Introduction to AI
- Understanding AI and current advancements
- AI development example
- Introduction to Responsible AI
- AI incident case study based on automotive applications
- EU AI Act
- Introduction to the EU AI Act
- Requirements for high-risk AI systems
- AI Development Standards
- ISO/IEC 42001:2023
- ISO/IEC 22989:2022
- ISO/IEC 5338:2023
- AI system lifecycle
- AI Management System Organization
- Context of the organization
- Leadership, roles and responsibilities
DAY 2
- AI Management System Inception
- AI policies
- AI objectives
- AI Management System Risk Management
- Performing risk management
- Applying risk treatment and AI controls
- Conducting an AI system impact assessment
- AI Management System Verification and Validation
- Performance evaluation
- Verification and validation
- Deployment
- AI Management System Improvement
- Nonconformity assessment
- Corrective action
- Internal and External audits
