Summary:
Le 6 novembre, la Commission européenne a tenu sa première réunion plénière pour commencer à travailler sur un code de conduite volontaire pour le marquage et l’étiquetage des contenus générés par l’IA, visant à soutenir les exigences de transparence du règlement européen sur l’IA. L’objectif de cette initiative est d’assurer que les obligations de transparence énoncées dans le règlement européen sur l’IA sont mises en œuvre de manière efficace et de faciliter la conformité pour les fournisseurs et les déployeurs d’IA. Les points clés incluent un processus de rédaction de sept mois qui intègre une consultation publique, deux groupes de travail axés sur les obligations des déployeurs et des fournisseurs, et un alignement avec l’article 50 du règlement européen sur l’IA, qui sera exécutoire en août 2026. Le processus devrait se conclure en mai ou juin 2026.
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The European Union (EU) has taken a significant step towards enhancing the transparency of AI-generated content by initiating work on a voluntary code of practice. This initiative, announced by the EU Commission, aligns with the EU Artificial Intelligence Act’s provisions, specifically addressing Article 50, which mandates transparency obligations for AI systems. Article 50 emphasizes the importance of informing users when they interact with AI-generated content, a safeguard designed to prevent deception and ensure trust in AI technologies. With the enforcement of the EU AI Act scheduled for August 2026, this code of practice could serve as an essential tool to operationalize these requirements effectively.
The development of this code of practice will unfold through two dedicated working groups. One group will concentrate on the obligations of providers—companies that create and supply AI systems—and the other will focus on deployers—entities utilizing AI systems in real-world applications. This dual approach acknowledges the distinct roles and responsibilities of these parties in ensuring transparency. To gather wide-ranging perspectives, the EU Commission has initiated a public consultation, a mechanism often employed to incorporate diverse stakeholder views into policymaking. The drafting process is expected to conclude by May-June 2026, enabling sufficient time for implementation ahead of the AI Act’s enforceability.
The legal context of this effort cannot be understated. The EU AI Act is poised to be one of the most comprehensive regulatory frameworks for Artificial Intelligence globally. Inspired by precedents like the General Data Protection Regulation (GDPR), the Act aims to enhance transparency, accountability, and fairness in AI deployment across various sectors. The voluntary nature of the code of practice mirrors other international initiatives, such as the Global Partnership on Artificial Intelligence (GPAI), which has similarly opted for non-binding codes to encourage compliance without imposing rigid mandates. Nevertheless, voluntary guidelines often carry the risk of minimal compliance, raising concerns among experts about the effectiveness of the EU’s approach.
From an ethical standpoint, the push for precise transparency rules is crucial in mitigating risks associated with generative AI technologies, such as misinformation, manipulation, and the misuse of synthetic media. By explicitly requiring clear labeling and marking of AI-generated content, the EU can enhance individual autonomy, ensuring users can discern whether the information they are engaging with originated from a human or a machine. Such measures also support the ethical principle of informed consent and prevent ‘dark patterns’—design practices that manipulate user decisions—which have been a growing concern in digital governance. For instance, China’s newly established transparency rules for generative AI provide detailed guidance on how notices should appear, including specifications for both digital and physical formats. These requirements serve as a potential benchmark for how the EU might frame its code to ensure accountability and clarity.
The implications for industry stakeholders are vast. For providers of generative AI systems, the code offers a pathway to demonstrate compliance with the forthcoming legal standards, helping to build trust among users and partners. Companies like OpenAI, which develop large-scale language models, or smaller European start-ups entering this space, may find that adherence to a clear, well-crafted code of practice gives them a competitive edge in the increasingly regulated AI landscape. Deployers, such as e-commerce platforms, search engines, or marketing firms utilizing generative AI, will need to navigate the complexities of merging operational convenience with transparency requirements. They may need to adopt user-friendly methods, such as prominently displaying disclaimers whenever AI is employed in creating content, ensuring clarity without compromising user experience.
Overall, while challenges remain—such as incentivizing adoption given its non-mandatory nature—the EU’s ongoing efforts are a testament to its commitment to ethical AI governance. If executed correctly, the code has the potential to become a global gold standard, fostering a culture of transparency that reduces risks while enabling innovation in the AI field.