**Target:** Proposal for a regulation — Recital 60 g (new)

## Text proposed by the Commission



(60g)

## Amendment of the European Parliament

(60g) In light of the nature and complexity of the value chain for AI system, it is essential to clarify the role of actors contributing to the development of AI systems. There is significant uncertainty as to the way foundation models will evolve, both in terms of typology of models and in terms of self-governance. Therefore, it is essential to clarify the legal situation of providers of foundation models. Combined with their complexity and unexpected impact, the downstream AI provider’s lack of control over the foundation model’s development and the consequent power imbalance and in order to ensure a fair sharing of responsibilities along the AI value chain, such models should be subject to proportionate and more specific requirements and obligations under this Regulation, namely foundation models should assess and mitigate possible risks and harms through appropriate design, testing and analysis, should implement data governance measures, including assessment of biases, and should comply with technical design requirements to ensure appropriate levels of performance, predictability, interpretability, corrigibility, safety and cybersecurity and should comply with environmental standards. These obligations should be accompanied by standards. Also, foundation models should have information obligations and prepare all necessary technical documentation for potential downstream providers to be able to comply with their obligations under this Regulation. Generative foundation models should ensure transparency about the fact the content is generated by an AI system, not by humans. These specific requirements and obligations do not amount to considering foundation models as high risk AI systems, but should guarantee that the objectives of this Regulation to ensure a high level of protection of fundamental rights, health and safety, environment, democracy and rule of law are achieved. Pre-trained models developed for a narrower, less general, more limited set of applications that cannot be adapted for a wide range of tasks such as simple multi-purpose AI systems should not be considered foundation models for the purposes of this Regulation, because of their greater interpretability which makes their behaviour less unpredictable.

In light of the nature and complexity of the value chain for AI system, it is essential to clarify the role of actors contributing to the development of AI systems. There is significant uncertainty as to the way foundation models will evolve, both in terms of typology of models and in terms of self-governance. Therefore, it is essential to clarify the legal situation of providers of foundation models. Combined with their complexity and unexpected impact, the downstream AI provider’s lack of control over the foundation model’s development and the consequent power imbalance and in order to ensure a fair sharing of responsibilities along the AI value chain, such models should be subject to proportionate and more specific requirements and obligations under this Regulation, namely foundation models should assess and mitigate possible risks and harms through appropriate design, testing and analysis, should implement data governance measures, including assessment of biases, and should comply with technical design requirements to ensure appropriate levels of performance, predictability, interpretability, corrigibility, safety and cybersecurity and should comply with environmental standards. These obligations should be accompanied by standards. Also, foundation models should have information obligations and prepare all necessary technical documentation for potential downstream providers to be able to comply with their obligations under this Regulation. Generative foundation models should ensure transparency about the fact the content is generated by an AI system, not by humans. These specific requirements and obligations do not amount to considering foundation models as high risk AI systems, but should guarantee that the objectives of this Regulation to ensure a high level of protection of fundamental rights, health and safety, environment, democracy and rule of law are achieved. Pre-trained models developed for a narrower, less general, more limited set of applications that cannot be adapted for a wide range of tasks such as simple multi-purpose AI systems should not be considered foundation models for the purposes of this Regulation, because of their greater interpretability which makes their behaviour less unpredictable.