Intelligence artificielle

Two centuries of technological progress have redefined society, as industrial and digital automation have modified how people live, work, and how we interact with each other. What began with mechanised production lines to increase efficiency has evolved into autonomous and semi-autonomous systems capable of analysing data and making decisions with minimal human involvement. Propelled by breakthroughs in Artificial Intelligence (AI) - such as deep learning and transformer architectures - this automation now spans a wide range of sectors, including healthcare, finance, military defence, transportation, and public administration.

The International Working Group on Data Protection in Technology (Berlin Group) met in Tbilisi, Georgia, on 2–3 July 2025.

Following you can find the documents adopted during this event:

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.