The development of an artificial intelligence system requires rigorous management and monitoring of training data. The CNIL details how data protection principles relate to training data management.

In view of their potential benefits, open source practices should be considered when assessing legitimate interests of an AI system provider. However, it is necessary to adopt safeguards to limit the…

The data annotation phase is crucial to ensure the quality of the AI model. This challenge can be achieved by means of a rigorous methodology guaranteeing performance for the system and protection of…

Controllers will most commonly rely on their legitimate interests for the development of AI systems. However, this legal basis cannot be used without respecting its conditions and implementing…

The security of AI systems is an issue too often overlooked by their designers. However, it remains an obligation to guarantee data protection both during the development of the system and in…