AI Standardization

duration | 3 days

Description

Course on standardization: what is it, Bodies structure, modus operandi, how to collaborate, how to adopt, impact.

Learning Outcomes

By the end of the course, participants will be able to:

  • Understand the Role and Relevance of Standardization in AI
    • Explain what standardization is and why it matters in the context of AI.
    • Identify key benefits, limitations, and implications of standards for AI development, deployment, and governance.
  • Recognize the Landscape of AI Standards
    • Navigate international, European, and national standardization bodies involved in AI (e.g., ISO/IEC JTC 1/SC 42, CEN-CENELEC, IEEE).
    • Identify core categories of AI standards: terminology, risk management, quality, trustworthiness, data governance, etc.
  • Apply Key Standards and Frameworks to Real-World Scenarios
    • Interpret and apply relevant AI standards to specific use cases (e.g., trustworthy AI, human oversight, transparency).
    • Understand how standards support regulation (e.g., EU AI Act conformity assessments).
  • Engage in Standardization Activities
    • Understand how organizations and experts contribute to standard development.
    • Identify how to participate or influence standardization efforts in their sector or region.
  • Anticipate Gaps and Future Needs in AI Standardization
    • Recognize limitations of existing standards for emerging technologies and contexts.
    • Develop strategies to identify standardization gaps and engage in future-forward planning.

Introduction to Standardization and its Relevance to AI

duration | 3 hours

Learning Outcomes

  • Define standardization and its strategic role in AI
  • Understand the relationship between standards, innovation, and compliance

Activities

  • Lecture with discussion: “Why do AI standards matter?”
  • Timeline exercise: History of AI standardization milestones
  • Poll: Perceptions of standards in innovation

The AI Standards Landscape

duration | 4 hours

Learning Outcomes

  • Identify key standardization bodies and frameworks
  • Classify different types of AI-related standards

Activities

  • Mapping activity: Who does what in AI standardization
  • Standards walkthrough: ISO/IEC 22989 (AI Concepts), ISO/IEC 24028 (Trustworthiness)
  • Case discussion: Alignment with the EU AI Act

Applying Standards in Practice

duration | 4 hours

Learning Outcomes

  • Use AI standards to guide technical or organizational processes
  • Link AI lifecycle stages with relevant standardization measures

Activities

  • Use case review: Evaluating a predictive maintenance system using trustworthiness criteria
  • Group activity: Drafting conformity evidence for an AI system
  • Quiz

Engagement and Participation in Standardization

duration | 3 hours

Learning Outcomes

  • Understand the standard development process
  • Identify how to get involved or contribute to committees

Activities

  • Process simulation: Participating in a technical committee
  • Role-play: Debating clauses in a draft standard
  • Group reflection: Opportunities for participation

Gaps, Challenges, and the Future of AI Standardization

duration | 4 hours

Learning Outcomes

  • Recognize areas where existing standards fall short
  • Strategize ways to anticipate future standardization needs

Activities

  • Horizon scanning: Exploring upcoming AI technologies
  • SWOT analysis of current AI standardization efforts
  • Final project: Suggesting a new area for standard development