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Certificate Course / R*AI

2026 Certificate Course Responsible AI

Learning Responsible AI from and with professionals

Location: Online
Dates: November 6, November 13, November 20, November 27, 2026
Application by August 15, 2026

The course is organized by the AI competence centers in Germany (BIFOLD, DfKI, Lamarr Institute, 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.

 

Apply for the Certificate Course

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. 

Prof. Dr. Eva Schmidt

TU Dortmund / Lamarr Institute

Prof. Dr. Wojciech Samek

Fraunhofer HHI / TU Berlin / BIFOLD

Agenda

Time Description
09:00 Introduction / Get to know
09:30 Keynote – Responsible AI - A Philosophical Perspective
Eva Schmidt (Lamarr Institute)
10:30 Break
10:45 Data-Centric Responsible AI: Automated Validation & Debugging
Sebastian Schelter (BIFOLD)
11:45 Break
12:15 Identifying and Mitigating Bias in LLM Training Data: From EU AI Act Requirements to Practical Approaches
Rebekka Görge (Lamarr Institute)
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 Institute)
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

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