Artificial Intelligence

The work item will be a domain-specific focus application of the EN 304 223 principle for base cybersecurity requirements for AI models and systems to Generative AI. The TS will focus on the subject of deepfakes, which includes the issues of misinformation, disinformation, loss of confidentiality, copyright, IPR and the training/source material for LLMs. Also, this TS will include more prescriptive specifications for this domain extension to EN 304 223 when necessary.  

This document describes a taxonomy of the AI tasks related to computer vision. It includes AI tasks pertaining to either the analysis or generation of images and videos.

The pace of innovation in AI methods, architectures and tools remains exceptionally high, driven by progress in data availability, computational capacity and algorithmic development. As a result, the professional landscape surrounding AI is in constant evolution: new roles, specialisations and skill requirements emerge, while others evolve, merge or decline in relative importance. 

This CEN Workshop Agreement (CWA) is intended to function as a living reference point: a common baseline that can support dialogue, alignment and comparability, while remaining open to revision as the AI field continues to mature and transform. Readers and users of this document are encouraged to interpret and apply it with this dynamic context in mind, recognising both its value as a shared framework and its limitations in a field defined by rapid and ongoing change. 

This CWA is partially based on the results of the Artificial Intelligence Skills Alliance (ARISA) project, funded under the Erasmus+ programme ‘Partnerships for Innovation; Alliances for Sectoral Cooperation on Skills’ of the European Commission.

This document describes common capabilities, requirements and a supporting information model for logging of events in AI systems. This document is designed to be used with a risk management system.