Model Reporting for Certifiable AI: A Proposal from Merging EU Regulation into AI Development
Abstract
Despite large progress in Explainable and Safe AI, practitioners suffer from a lack of regulation and standards for AI safety. In this work we merge recent regulation efforts by the European Union and first proposals for AI guidelines with recent trends in research: data and model cards. We propose the use of standardized cards to document AI applications throughout the development process. Our main contribution is the introduction of use-case and operation cards, along with updates for data and model cards to cope with regulatory requirements. We reference both recent research as well as the source of the regulation in our cards and provide references to additional support material and toolboxes whenever possible. The goal is to design cards that help practitioners develop safe AI systems throughout the development process, while enabling efficient third-party auditing of AI applications, being easy to understand, and building trust in the system. Our work incorporates insights from interviews with certification experts as well as developers and individuals working with the developed AI applications.
Cite
@article{arxiv.2307.11525,
title = {Model Reporting for Certifiable AI: A Proposal from Merging EU Regulation into AI Development},
author = {Danilo Brajovic and Niclas Renner and Vincent Philipp Goebels and Philipp Wagner and Benjamin Fresz and Martin Biller and Mara Klaeb and Janika Kutz and Jens Neuhuettler and Marco F. Huber},
journal= {arXiv preprint arXiv:2307.11525},
year = {2023}
}
Comments
54 pages, 1 figure, to be submitted