- Technical Contributions to WG2 & WG4's Draft Standards through Annex ZA and hEN Checklists
Artificial Intelligence
I believe that this work helps reduce compliance uncertainty and costs for SMEs. Technical coherence across the standards framework simplifies implementation for organizations with limited resources. My contributions to the QMS standard particularly focus on ensuring requirements are scalable and accessible to SMEs developing AI systems (i.e. being able to show SMEs how standard interrelating is valuable and would solve burdens related to understanding how requirements across different standards flow).
The work on the AI Trustworthiness Framework (particularly enhancing requirements for transparency and human oversight) ensures standards effectively support the protection of fundamental rights as required by the AI Act. This strengthens societal safeguards against potential harms from AI systems.
- Co-editing AI Trustworthiness Framework prEN 18229 and coordinating across JTC21 Working Groups
Artificial Intelligence
The editorial leadership of EN AI Trustworthiness Framework Part II directly supports European SMEs through Articles 62-63 AI Act provisions for SME assistance. The standard provides SMEs with clear, pre-endorsed technical specifications for meeting AI Act accuracy and robustness requirements, reducing compliance costs and legal uncertainty. The harmonization documentation coordinated through editorial work enables SMEs to achieve presumption of conformity through standardized approaches rather than expensive individual assessments.
I can see several societal impacts with the engaged standadisation activities: AI Accuracy and Robustness Standards: As Editor of EN AI Trustworthiness Framework Part II, my work directly supports European citizens' rights to accurate and robust AI systems. The standard establishes technical requirements ensuring AI systems deployed across the EU meet rigorous accuracy standards and maintain performance across operational conditions, protecting citizens from unreliable algorithmic decision-making in high-risk contexts. SME Innovation Ecosystem: The editorial leadership through N1106 coordination enables European SMEs to compete effectively in AI markets by providing clear compliance pathways rather than costly regulatory uncertainty. This supports innovation while ensuring responsible AI deployment protecting European citizens. European Leadership in Global AI Governance: The editorial role positions European values-based approaches to AI accuracy and robustness for global influence. The framework embeds principles of reliability, trustworthiness, and accountability into technical specifications that influence international AI standardization discussions. Consumer Protection Framework: The cross-WG coordination through N1106 ensures AI standards address consumer concerns around system reliability, performance consistency, and safety while remaining technically implementable. This balance protects European consumers while supporting technological advancement and maintaining Europe's competitive position in global AI markets.
Value of Research
My fellowship addresses three critical gaps in the European AI standardization landscape: The first gap concerns the harmonisation of Documentation Development, as there is an urgent need for technical documentation (Annex ZA, HAS checklists) to connect developing standards with AI Act requirements following the M/593 request. Without this work, standards risk delayed OJEU citation, creating regulatory uncertainty. I've worked on developing preliminary harmonization documents for JT021008 (Trustworthiness), JT021039 (QMS), and JT021024 (Risk Management).
