| Title | Time | Room | Teacher |
|---|---|---|---|
| AI-Playground | 13.01.2027 17:00 - 19:00 (Wed) | Online | Dr. Daniel Kunzelmann |
| AI-Playground | 20.01.2027 17:00 - 19:00 (Wed) | Online | Dr. Daniel Kunzelmann |
| AI-Playground | 27.01.2027 17:00 - 19:00 (Wed) | Online | Dr. Daniel Kunzelmann |
Artificial intelligence is fundamentally reshaping everyday research – including doctoral work. It offers fascinating possibilities: from drafting and structuring academic texts, to organising and analysing literature, through to visualising and communicating complex results. At the same time, new questions and challenges arise: where can AI offer meaningful support, and where do we encounter limits, uncertainty – and grey areas?
This workshop is aimed at anyone who wants to explore AI’s potential, reflect on it critically and use it purposefully in their research. The idea is to learn from one another and discover new things together – from lesser-known AI applications and smart prompting to skilfully combining different tools.
The focus is on peer exchange, practice-oriented tool sharing and the joy of experimentation. Together, we test and discuss how AI can enrich the doctoral process – and when critical reflection is called for.
Workshop content:
- Short introduction: What is AI?
- Tool exchange: Which AI systems do we use?
- How-to-AI: How can we use these tools effectively?
- Discussion: opportunities, risks and grey areas
The course thrives on open exchange, where everyone can contribute their questions, experiences, favourite tools and practical tips.
Between the three varied live sessions, participants can test what has been discussed directly in their own projects – enabling a transfer of AI into everyday research that is both playful and effective.
No prior knowledge is required. Everyone is warmly welcome – whether you are just starting out as an AI “newbie” or would like to discuss detailed questions with other “heavy users”.
- Participants reflect on how they use AI in their everyday research.
- They broaden their knowledge of AI applications in the context of doctoral work.
- They learn to use AI tools in a creative and responsible way.
- They develop practical strategies for the effective use of AI tools.
- They benefit from peer exchange and share their own experiences.
The course is designed to be interactive. A mix of practice-oriented input and exercises in individual, pair and group work creates a lively learning process. There is also dedicated space for sharing experiences and discussion. The workshop concept combines the benefits of face-to-face interaction and innovative online elements (collaboration tool “Miro”). The training is output-oriented: participants have the opportunity to apply the tools and concepts presented directly in their own practice after each session and adapt them to their specific needs. The two follow-up sessions are dedicated to sharing experiences from these AI experimentation phases and to deepening selected topics. In addition, participants receive a handout, a visual summary of the outcomes and a certificate of attendance.
At the beginning of the doctorate │ during the doctorate │ at the end of the doctorate
None.
Laptop/tablet with stable internet connection, microphone, webcam, Zoom (in most cases).
Dr. Daniel Kunzelmann is a qualified trainer in digital workflow with many years of experience. He delivers scientifically grounded, practice-oriented training on stress, resilience, time competence and self‑management. Since 2013, he has been teaching and conducting research at the University of Basel. His current research focuses on the negative effects of digitalisation on our satisfaction, well‑being and productivity.