Intelligence artificielle

The 5th G7 Data Protection and Privacy Authorities Roundtable took place on 18 to 19 June in Ottawa, Canada.

Following you can find the documents adopted during this event:

Federated Learning (FL) presents a promising approach to machine learning (ML) by allowing multiple sources of data (devices or entities) to collaboratively train a shared model while keeping data decentralised. This approach mitigates privacy risks as raw data remains locally on the sources, which is particularly beneficial in scenarios where data sensitivity or regulatory requirements make data centralisation[1] impractical. Applications of FL are diverse, spanning personalised recommendations, healthcare data analysis, data spaces, and autonomous transport systems, where ensuring privacy and data protection is paramount.

Speech by the EDPS Secretary General, Leonardo Cervera Navas, at CPDP - Data Protection Day.

On 13 November 2024, the European AI Office launched a multi-stakeholder consultation on the application of the definition of an AI system and the prohibited AI practices established in the AI Act. With this contribution, the EDPS would like to highlight possible discrepancies of the processing of personal data in the context of the development and deployment of certain AI systems with data protection law (without prejudice to these being finally assessed by national Courts and by the CJEU). This contribution builds on the EDPB and EDPS Joint Opinion on the AI Act, as well as relevant EDPB guidelines, and follows the structure of the questions included in the multi-stakeholder consultation.