AI governance professional training - gouvernance de l-IA

Introduction
Module 1: Foundations of artificial intelligence

Defines AI and machine learning, presents an overview of the different types of AI systems and their use cases, and positions AI models in the broader socio-cultural context.
Module 2: AI impacts on people and responsible AI principles

Outlines the core risks and harms posed by AI systems, the characteristics of trustworthy AI systems, and the principles essential to responsible and ethical AI.
Module 3: AI development life cycle

Describes the AI development life cycle and the broad context in which AI risks are managed.
Module 4: Implementing responsible AI governance and risk management

Explains how major AI stakeholders collaborate in a layered approach to manage AI risks while acknowledging AI systems' potential societal benefits.
Module 5: Implementing AI projects and systems

Outlines mapping, planning and scoping AI projects, testing and validating AI systems during development, and managing and monitoring AI systems after deployment.
Module 6: Current laws that apply to AI systems

Surveys the existing laws that govern the use of AI, outlines key GDPR intersections, and provides awareness of liability reform.
Module 7: Existing and emerging AI laws and standards

Describes global AI-specific laws and the major frameworks and standards that exemplify how AI systems can be responsibly governed.
Module 8: Ongoing AI issues and concerns

Presents current discussions and ideas about AI governance, including awareness of legal issues, user concerns, and AI auditing and accountability issues.

Conclusion