Description
The workshop aims to raise awareness for the importance of technical standardization in the field of information and communication technology, particularly in the field of artificial intelligence (AI). During the workshop the participants will develop AI applications (image classification) in Cloud resources, where they can concretely apply technical standardization using practical use cases.
Targeted Audience
IT or non-IT professionals with basic knowledge of AI as well as the associated standardization and digital trust aspects.
Learning outcomes and objectives
- Discover some good practices towards a responsible approach of AI projects within an organization
- Understand the fundamentals of AI, namely in the field of image classification
- Learn the good practices related to AI system lifecycle (for example, data usage, model training, system testing) based on standards
- Understand how to address some trustworthiness risks (for example, bias, robustness) based on the inputs from standards
- Identify relevant standards and efficiently apply them in AI projects
- Be able to contribute to technical standards
Program
Good practices supporting the development of AI projects within an organization
- ISO/IEC 42001:2023 Information technology — Artificial intelligence — Management system
- ISO/IEC TR 24028:2020 Information technology — Artificial intelligence — Overview of trustworthiness in artificial intelligence
- ISO/IEC TR 24368:2022 Information technology — Artificial intelligence — Overview of ethical and societal concerns
- prCEN/CLC/TR 17894 Artificial Intelligence Conformity Assessment
Overview of artificial intelligence
- EN ISO/IEC 22989:2023 Information technology — Artificial intelligence — Artificial intelligence concepts and terminology
- EN ISO/IEC 23053:2023 Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML)
Practical session
- Learn how to use Cloud resources
- Learn the good practices related to AI system lifecycle (for example, data usage, model training, system testing) using some international standards:
- Data usage
- ISO/IEC 8183:2023 Information technology — Artificial intelligence — Data life cycle framework
- ISO/IEC 5259 series on Data quality for analytics and machine learning (ML)
- ML model development
- ISO/IEC TR 24372:2021 Information technology — Artificial intelligence (AI) — Overview of computational approaches for AI systems
- System testing
- ISO/IEC AWI TS 29119-11 Information technology — Artificial intelligence — Part 11: Testing for AI systems
- ISO/IEC 4213:2022 Information technology — Artificial intelligence Assessment of machine learning classification performance
- Data usage
Standards development process
- Overview of ISO/IEC JTC 1/SC 42 Artificial Intelligence
- Overview of CEN/CLC JTC 21 Artificial Intelligence
- Overview of ISO/IEC JTC 1/SC 38 Cloud computing and distributed platforms
- How to follow and contribute to standards development
- How to consult standards
Duration
7 hours (including 1 hour for lunch)
Certificate
A certificate of participation issued by ILNAS, a recognized training organization, will be provided at the end of the course.