Code of Practice on Transparency of AI-Generated Content (marcatura ed etichettatura dei contenuti generati o manipolati dall'IA)

LEGAL TEXT: Article 50(2) and recital 133 AI Act

2. […] Providers shall ensure their technical solutions are effective, interoperable, robust and reliable as far as this is technically feasible, taking into account the specificities and limitations of various types of content, the costs of implementation and the generally acknowledged state of the art, as may be reflected in relevant technical standards.

In order to fulfil their obligation under Article 50(2) AI Act to ensure the employed technical solutions for marking and detection of AI-generated or manipulated content are effective, interoperable, robust and reliable, as far as this is technically feasible and taking into account the specificities and limitations of various types of content, the costs of implementation and the generally acknowledged state of the art, Signatories commit to ensure that their marking and detection solutions comply with the quality requirements described in the following measures, holistically across all marking techniques employed rather than for each technique individually. Signatories commit to assess and demonstrate compliance with the requirements in accordance with the testing, verification, and compliance processes specified in Commitment 4 prior to placing their generative AI system on the market or putting it into service, and throughout its lifecycle. Signatories commit to strive to achieve the best possible balance between effectiveness, interoperability, robustness and reliability of the marking and detection solutions as described in Measures 3.1 to 3.4 below. Operational constraints may impose limitations on computational

time and resources, costs of implementation, as well as on scalability to very large or very small content.