Certificate Course
Certificate Course on Responsible AI - Part 3
Organized by the German National AI Centers
20.11.2026
9:00 am - 2:30 pm
Online
The course is organized by the AI competence centers in Germany (BIFOLD, DfKI, Lamarr, MCML, ScaDS.AI and Tübingen AI Center). Researchers from several disciplines will work in pairs during four different thematic days to provide insight into cutting-edge AI research, highlighting their diverse perspectives on Responsible AI. Together, they paint a diverse and multifaceted picture that opens up space for independent thinking and collaborative discussion among teachers and learners. The course does not aim to provide a comprehensive catalog of knowledge on Responsible AI, but rather to foster the development of critical thinking and judgment skills with high expertise that enable independent further reflection.
Responsible AI?
Artificial intelligence is a game changer that will bring about lasting change in society. There is a consensus that this new technology must be used responsibly, but what that means in detail is far less clear. Is it about responsible development, responsible developers, responsible application, individual responsibility, or a legal framework based on the concept of responsibility? Is it about technical aspects such as fairness, transparency, explainability, and security? Or is it about legal aspects such as the development of a good framework or compliance with the EU AI Act? Or is it perhaps about the personal mindset of everyone involved?
Responsible AI as a Systemic Concept
If we understand “responsibility” systemically, we must say that all of the aspects mentioned are correct and important, and only when viewed together can they fulfill the claim of “Responsible AI.” Responsible AI is therefore precisely the interaction of the various technical, legal, ethical, and social aspects. This idea is at the heart of the certificate course “Responsible AI.” Researchers from various disciplines present their understanding of responsible AI, learn about approaches from other disciplines, and gain a broader perspective on their research. The approach of joint research-based teaching and learning guarantees an intensive exchange of ideas.
Prerequisites
The course is open for PhD students with a background in informatics, data sciences, machine learning or related. Interested participants from related fields are welcome to participate. Please provide information on your professional background and personal motivation in the registration form (see below).
The course consists of four full days, all of which must be entirely attended via online platforms. Active participation and, where applicable, the completion of small assignments are also expected. Upon successful completion (under the specified conditions), participants will receive a certificate issued by the AI competence centers confirming their successful participation.
Program
9:00 am – 11:30 am
Algorithmic Fairness
Christoph Kern / Jan Simson (MCML)
11:30 am – 12:30 pm
Privacy, Utility, and Trust in Synthetic Biomedical Data
Hakime Öztürk (EMBL)
12:30 pm – 1:00 pm
1:00 pm – 2:00 pm
Privacy and Security Challenges in Agentic AI
Annika Hannemann (Swiss Centre for Responsible AI (SCRAI))
2:00 pm – 2:30 pm
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