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Oral
in
Workshop: Regulatable ML: Towards Bridging the Gaps between Machine Learning Research and Regulations

Merging (EU)-Regulation and Model Reporting

Danilo Brajovic · Vincent Philipp Göbels · Janika Kutz · Marco Huber


Abstract:

Regulating AI systems remains a complex and unsolved issue despite years of active research. Various governmental approaches are currently underway, with the European AI Act being a significant initiative in this domain. In the absence of official regulations, researchers and developers have been exploring their own methods to ensure the secure application of AI systems. One well-established practice is the usage and documentation of AI applications through data and model cards. Although data and model cards do not explicitly address regulation, they are widely adopted in practice and share common characteristics with regulatory efforts. This paper presents an extended framework for reporting AI applications based on use-case, data, model and deployment cards, specifically designed to address upcoming regulations by the European Union. The proposed framework aligns with industry practices and provides comprehensive guidance for regulatory compliance and transparent reporting. By documenting the development process and addressing key requirements, the framework aims to support the responsible and accountable deployment of AI systems in line with EU regulations, positioning developers well for future legal requirements.

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