2026 Certificate Course Responsible AI
Location: Online
Dates: November 6, November 13, November 20, November 27, 2026
Application by August 15, 2026
Learning Responsible AI from and with professionals
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.
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Keynotes & Speakers
The three keynote speeches are given by leading scientists and provide introductory insights into specific topics in Machine Learning, Data Management, Robotics, and the societal implications of AI in the context of the design of Autonomous Systems. The keynote speeches allow participants from all disciplines to broaden their interdisciplinary skills and understanding.
Certificate Course
Agenda
The 2026 Summer School will present a variety of formats and takes place over 3.5 days. In the following you will find the schedule for each day. Please note that on several days parallel content tracks are prepared.
| Time | Description | ||
|---|---|---|---|
| 09:00 | Introduction / Get to know | ||
| 09:30 | Keynote – Responsible AI - A Philosophical Perspective Eva Schmidt (Lamarr) | ||
| 10:30 | Break | ||
| 10:45 | Data-Centric Responsible AI: Automated Validation & Debugging Sebastian Schelter (BIFOLD) | ||
| 11:45 | Break | ||
| 12:15 | Bias in LLMs und ihre Mitigation Rebekka Görge (Lamarr) | ||
| 13:15 | Break | ||
| 13:30 | Joint Discussion | ||
| 14:30 | End Day One | ||
| Governance | |||
|---|---|---|---|
| Time | Description | ||
| 09:00 | Beyond Rigid Specification: Justifiability as Approach to Responsible AI Kevin Baum / Anne Lauber Rönsberg (DFKI / ScaDS.AI) | ||
| 11:30 | Operationalisierung der KI-Verordnung Maximilian Poretschkin (Lamarr) | ||
| 12:30 | Pause | ||
| 13:00 | AI / Law Michael Tiemann (Tübingen AI Center) | ||
| 14:00 | Joint Discussion | ||
| 14:30 | End Day 2 | ||
| Fairness and privacy in practice: Concepts, trade-offs and challenges | |||
|---|---|---|---|
| Time | Description | ||
| 09:00 | Algorithmic Fairness Christoph Kern / Jan Simson (MCML) | ||
| 11:30 | Privacy, Utility, and Trust in Synthetic Biomedical Data Hakime Öztürk (EMBL) | ||
| 12:30 | Pause | ||
| 13:00 | Privacy and Security Challenges in Agentic AI Annika Hannemann (Swiss Centre for Responsible AI (SCRAI)) | ||
| 14:00 | Joint Discussion | ||
| 14:30 | End Day Three | ||
| From explainable to ethical AI | |||
|---|---|---|---|
| Time | Description | ||
| 09:00 | Keynote – Explainable AI Wojciech Samek (BIFOLD) | ||
| 10:00 | Responsible AI in applied protein design Anne Schmieder / Hermann Diebl-Fischer / Clara Schoeder (ScaDS.AI) | ||
| 11:00 | Ethics as an Added Value in Responsible AI Development Mihai Maftei / Hartmut Hilpert (DFKI) | ||
| 13:30 | Pause | ||
| 14:00 | Joint Discussion | ||
| 14:30 | End of last Day | ||
What to expect
KEYNOTES
The keynote speeches are intended to provide an introductory overview of specific topics in Machine Learning, Data Management, Robotics, and the societal impact of AI in the context of the responsible design of AI-driven autonomous systems.
IN-DEPTH SESSIONS
In-Depths Lectures give a detailed introduction to specific topics, methods and projects of state-of-the-art research related to the design of autonomous systems in the various disciplines. Participants will be able to choose from parallel sessions according to their field of interest.
HANDS-ON SESSIONS
This practice-oriented formats offer participants hands-on experience and the opportunity to interact. Participants will be able to choose from parallel sessions according to their field of interest.
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