IWGDPT Berlin Group Meeting 2025 - Georgia
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:
Künstliche Intelligenz ist Realität und ist mit Navigationssystemen, Spamfiltern, Wettervorhersagen – um nur einige Beispiele zu nennen – bereits in unser alltägliches Leben vorgedrungen.
Auf dem Gebiet des maschinellen Lernens, einem Teilbereich der künstlichen Intelligenz, sind erhebliche Fortschritte zu verzeichnen. Die Maschinen lernen mithilfe komplexer Algorithmen, die es ihnen ermöglichen, riesige Datensätze zu analysieren und auf Grundlage dieser Daten Prognosen zu treffen. Parallel zur fortlaufenden Verbesserung der Fähigkeiten dieser Maschinen werden immer größere Datenmengen gesammelt und Informationen über menschliches Verhalten ausgewertet – all das stellt Herausforderungen für den Schutz der Privatsphäre und personenbezogener Daten dar.
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:
30 days of preserving privacy and data protection, what does that look like? Read our newsletter to register to our upcoming event on young people and children's privacy; our work in protecting people at EU borders, how we support AI innovation whilst protecting people's privacy and more!
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.