Today, the AI and Data Privacy and Security Training took place at the Jožef Stefan Institute in Ljubljana, bringing together more than 50 participants, including students, researchers, and innovators interested in trustworthy AI and data-driven technologies.

The event combined a scientific tutorial with a policy discussion, offering a comprehensive perspective on the technological and regulatory dimensions of modern AI systems.

The scientific session, “Knowledge Graph-Powered Decentralized Personalization”, was delivered by Oshani Seneviratne and Fernando Spadea from Rensselaer Polytechnic Institute. They introduced key concepts and practical approaches for building decentralized, privacy-aware AI systems, covering:

-- Personal Knowledge Graphs (PKGs) and their role in user-centric data modeling -- Federated learning and privacy-preserving computation -- Blockchain-based trust infrastructures -- Knowledge-graph-grounded Retrieval-Augmented Generation (RAG) pipelines

The tutorial also included a hands-on session, where participants worked with tools such as RDFLib, Flower, and LangChain to implement decentralized personalization workflows.

The event concluded with a policy session on the EU AI Act, delivered by Polona Pičman Štefančič from the Ministry of Digital Transformation, highlighting key regulatory aspects and their implications for AI development and deployment.

We would like to thank all speakers for their insightful contributions, and especially the participants for their active engagement and discussions throughout the day.