Legal Implications of Vision-Language Foundation Models (VLFM) in Industrial Applications in Europe: An Inquiry into Data Protection, Copyright, and AI Regulation
The rise of Foundation Models (FM) starts to revolutionize different aspects of machine vision in industrial applications. Increased generalizability, robustness, reliability, and the capacity for few-shot learning make vision systems adaptable and flexible to an unprecedented degree. Yet, the development and deployment of fine-tuned models in the industrial domain face unique legal challenges in Europe that arise from stringent regulations, including Copyright Law, the General Data Protection Regulation (GDPR), and the recently enacted AI Act. In this work, we investigate the legal implications of pre-training (1), fine-tuning (2), and utilizing VFMs (3) in industrial contexts in Europe, with a specific focus on manufacturing. With this contribution, we aim to raise awareness on how various regulations will impact the use of VLFMs in industrial settings.
Authors
- Thorsten Schüppstuhl (ORCID: https://orcid.org/0000-0002-9616-3976)
- Martin Gomse (ORCID: https://orcid.org/0000-0002-5555-1139)
- Keno Moenck (ORCID: https://orcid.org/0000-0003-3892-1588)
- Niklas Wais
- Boris Paal
Institutions
- Universität Hamburg (DE)
- Bavarian Research Institute for Digital Transformation (DE)
- Hamburg University of Technology (DE)
Publication Details
- Journal
- Procedia CIRP
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.procir.2025.02.223
- Primary Topic
- Digitalization, Law, and Regulation
- Type
- article
- Field-Weighted Citation Impact
- 0.00