Navigating the EU AI Act: A Methodological Approach to Compliance for Safety-critical Products

J. Kelly, S. Zafar, L. Heidemann, J. Zacchi, D. Espinoza +1 more
3/25/2024
cs.AI

No confident code implementation found for this paper.

Abstract

In December 2023, the European Parliament provisionally agreed on the EU AI Act. This unprecedented regulatory framework for AI systems lays out guidelines to ensure the safety, legality, and trustworthiness of AI products. This paper presents a methodology for interpreting the EU AI Act requirements for high-risk AI systems by leveraging product quality models. We first propose an extended product quality model for AI systems, incorporating attributes relevant to the Act not covered by current quality models. We map the Act requirements to relevant quality attributes with the goal of refining them into measurable characteristics. We then propose a contract-based approach to derive technical requirements at the stakeholder level. This facilitates the development and assessment of AI systems that not only adhere to established quality standards, but also comply with the regulatory requirements outlined in the Act for high-risk (including safety-critical) AI systems. We demonstrate the applicability of this methodology on an exemplary automotive supply chain use case, where several stakeholders interact to achieve EU AI Act compliance.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{kelly2024navigating,
  title  = {Navigating the EU AI Act: A Methodological Approach to Compliance for Safety-critical Products},
  author = {J. Kelly and S. Zafar and L. Heidemann and J. Zacchi and D. Espinoza and N. Mata},
  year   = {2024},
  eprint = {2403.16808},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2403.16808v2}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2403.16808.svg)](https://codeofpaper.com/paper/2403.16808)

Discussion