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Council of Europe Framework Convention on Artificial Intelligence: Context, Regulatory Approach and Scope of Obligations

Published online by Cambridge University Press:  17 December 2025

Vladislava Stoyanova*
Affiliation:
Faculty of Law, Lund University, Lund, Sweden
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Abstract

The Council of Europe has very recently adopted the Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law. This article provides an initial analysis of the CoE AI Convention. It emphasises the necessity of understanding the CoE AI Convention within the context of its adoption as an international treaty negotiated within the Council of Europe. This context has affected its scope in terms of how the treaty includes the regulation of the usage of AI systems by both public authorities and private actors. The detailed review of the available negotiation documents reveals that the concrete level of protection offered by the Convention has been lowered. This includes the risk-based approach, which shapes the obligations undertaken by States under the treaty. This approach is explained and contrasted with the approach under the EU AI Act. The argument that emerges is that the absence of categorisation of risk levels in the treaty is related to its higher level of abstraction, which does not necessarily imply less robust obligations. The content of these obligations is also clarified in light of the requirement imposed by the treaty of consistency with human rights law. An argument is advanced that the principles formulated in the treaty – human dignity and individual autonomy, transparency and oversight, accountability, non-discrimination, data protection, reliability, risk-management – can offer interpretative guidance for the development of human rights standards.

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Type
Articles
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press