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Without Fee

2026 Berlin Summer School of Artificial Intelligence and Society

Berlin (GER), June 2026 - How do you design AI systems that act autonomously while remaining safe, transparent, trustworthy, and accountable? Join the 2026 Berlin Summer School of Artificial Intelligence and Society in Berlin to explore this question. Places are limited to 50. Registration is mandatory. Applications close June 30, 2026.

The Berlin Summer School of Artificial Intelligence and Society 2026 on "Responsible design of AI-driven autonomous systems" takes place September 14–17, 2026, at Technische Universität Berlin. The 3.5-day program brings together early-career researchers from across the sciences to address foundational questions in the responsible development of autonomous AI systems.
The program focuses on core challenges at the intersection of autonomous systems, trustworthy machine learning, and robotics, as well as their deployment in critical domains such as healthcare and scientific infrastructures..

Program
The Summer School offers a range of formats: keynote speeches by leading researchers, in-depth lectures on current research topics, practice-oriented hands-on sessions, an excursion, and a poster session. Dedicated time for networking and interdisciplinary exchange is built into the program throughout.

Keynote Speakers
Prof. Dr. Iyad Rahwan, Max Planck Institute for Human Development
Prof. Dr. Judith Simon, Universität Hamburg / Deutscher Ethikrat
Prof. Dr. Marc Toussaint, Technische Universität Berlin

Participation
The Summer School is designed for doctoral and postdoctoral researchers from the Weizenbaum Institute, the Learning and Intelligent Systems research lab, and the network of German Centers of Excellence for AI (BIFOLD, DFKI, Lamarr, MCML, ScaDSAI, and TUEAI), as well as researchers from other universities and institutions. Final-year Master's students are also invited. Participants are expected to attend the full program. There is no participation fee; travel and accommodation costs are the responsibility of participants.