{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/design-of-a-quality-management-system-based","title":"Design of a Quality Management System based on the EU Artificial Intelligence Act","arxiv_id":"2408.04689","date":"2024-08-08","proceeding":null,"authors":["Henryk Mustroph","Stefanie Rinderle-Ma"],"abstract":"The EU AI Act mandates that providers and deployers of high-risk AI systems establish a quality management system (QMS). Among other criteria, a QMS shall help verify and document the AI system design and quality and monitor the proper implementation of all high-risk AI system requirements. Current research rarely explores practical solutions for implementing the EU AI Act. Instead, it tends to focus on theoretical concepts. As a result, more attention must be paid to tools that help humans actively check and document AI systems and orchestrate the implementation of all high-risk AI system requirements. Therefore, this paper introduces a new design concept and prototype for a QMS as a microservice Software as a Service web application. It connects directly to the AI system for verification and documentation and enables the orchestration and integration of various sub-services, which can be individually designed, each tailored to specific high-risk AI system requirements. The first version of the prototype connects to the Phi-3-mini-128k-instruct LLM as an example of an AI system and integrates a risk management system and a data management system. The prototype is evaluated through a qualitative assessment of the implemented requirements, a GPU memory and performance analysis, and an evaluation with IT, AI, and legal experts.","url_abs":"https://arxiv.org/abs/2408.04689v2","url_pdf":"https://arxiv.org/pdf/2408.04689v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"design-of-a-quality-management-system-based","repo_url":"https://github.com/henryk-mustroph/first_version_qmsaia","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"document-ai","task_name":"Document AI"},{"task_slug":null,"task_name":"GPU"},{"task_slug":"management","task_name":"Management"}],"methods":[{"method_slug":"attention","method_name":"Attention"},{"method_slug":"focus","method_name":"Focus"},{"method_slug":null,"method_name":null},{"method_slug":"softmax","method_name":"Softmax"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}