An interdisciplinary account of the terminological choices by EU policymakers ahead of the final agreement on the AI Act: AI system, general purpose AI system, foundation model, and generative AI

Author:

Fernández-Llorca David,Gómez EmiliaORCID,Sánchez Ignacio,Mazzini Gabriele

Abstract

AbstractThe European Union’s Artificial Intelligence Act (AI Act) is a groundbreaking regulatory framework that integrates technical concepts and terminology from the rapidly evolving ecosystems of AI research and innovation into the legal domain. Precise definitions accessible to both AI experts and lawyers are crucial for the legislation to be effective. This paper provides an interdisciplinary analysis of the concepts of AI system, general purpose AI system, foundation model and generative AI across the different versions of the legal text (Commission proposal, Parliament position and Council General Approach) before the final political agreement. The goal is to help bridge the understanding of these key terms between the technical and legal communities and contribute to a proper implementation of the AI Act. We provide an analysis of the concept of AI system considering its scientific foundation and the crucial role that it plays in the regulation, which requires a sound definition both from legal and technical standpoints. We connect the outcomes of this discussion with the analysis of the concept of general purpose AI system and its evolution during the negotiations. We also address the distinct conceptual meanings of AI system vs AI model and explore the technical nuances of the term foundation model. We conclude that rooting the definition of foundation model to its general purpose capabilities following standardised evaluation methodologies appears to be most appropriate approach. Lastly, we tackle the concept of generative AI, arguing that definitions of AI system that include “content” as one of the system’s outputs already captures it, and concluding that not all generative AI is based on foundation models.

Funder

HORIZON EUROPE Framework Programme

Publisher

Springer Science and Business Media LLC

Reference25 articles.

1. Abdin M, Jacobs SA, Awan AA, Aneja J, Awadallah A., Awadalla H, Bach N, Bahree A, Bakhtiari A, Behl H, et al.(2024). Phi-3 technical report: A highly capable language model locally on your phone. arXiv preprint: arXiv:2404.14219

2. Boine C, Rolnick D (2023) General purpose AI systems in the AI Act: trying to fit a square peg into a round hole. We Robot

3. Bommasani R, Bommasani R, Hudson DA, Adeli E, Altman R, Arora S, von Arx S, Bernstein MS, Bohg J, Bosselut A, Brunskill E, et al. (2021) On the opportunities and risks of foundation models, arXiv preprint: arXiv:2108.07258

4. Devlin J, Chang MW, Lee K, Toutanova K (2019) Bert: Pre-training of deep bidirectional transformers for language understanding. In North American Chapter of the Association for Computational Linguistics, pp. 4171–4186

5. Estevez Almenzar M, Fernández Llorca D, Gomez E, Martinez Plumez F (2022) Glossary of human-centric artificial intelligence. EUR 3113 EN, Publications Office of the European Union, Luxembourg, JRC129614. https://doi.org/10.2760/860665

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