* Keeping Track of Your AI: Organising, Reflecting and Documenting AI Use in Research (GGG) online

Trainer: The interactive online sessions are facilitated by Dr. Christian Steinau. Christian Steinau enjoys formats in which dialogue leads to concrete action. His academic home is LMU Munich, where he earned his doctorate on the topic of judgment: a skill that is becoming increasingly important in today’s work with AI. After all, the better AI systems become at producing texts, analyses, and ideas, the more important it becomes to consider how we evaluate, contextualize, and responsibly utilize their outputs. As the director of a Transfer Lab, he worked at the intersection of research, society, and application. In 2020, he founded the Cultural Policy Lab, which he has been leading since 2025 as a research firm specializing in the cultural and creative industries. His initiatives combine a curiosity about new technologies with scientific rigor, peer learning, and a clear focus on integrity and practical value.

Internal experts: In addition to the trainer, experts from the GWDG will be available for questions and exchange on internal AI tools and services.

Participants are warmly invited to contribute their own questions, experiences, tools, workflows and critical perspectives. The aim is to learn from one another, build networks across disciplines, and develop practical, reflective and future-oriented ways of working with AI in doctoral research.

In this session, you will explore simple ways to organise, reflect on, and document our own AI practices. Rather than trying to record every interaction, we will ask what is actually worth keeping – from useful prompts, reusable instructions and recurring workflows to information about the tools and models we use and how AI-generated outputs were checked, changed, or incorporated into our own work.

You will look at different ways of keeping track of AI use, such as prompt libraries, research or lab notebooks, version histories, and AI usage documentation. Working with concrete examples from your own research, we will consider what is useful to record, what may already be documented as part of existing research practices, and what others would need to know to understand the role AI played in a research process.

Together we will also connect these everyday documentation practices to more formal transparency requirements, including the University of Göttingen’s guidance on declaring AI use, and consider how good documentation can make it easier to prepare an AI transparency statement when needed.

Expect practical exercises, concrete examples, exchange with other researchers, and space to reflect on your own AI practices. The aim is not to create a perfect documentation system, but to identify simple approaches that can make your use of AI more organised, traceable, and easier to communicate.

All AI Sessions of GGG are not designed as a conventional training courses. Instead, they create a regular forum for exchange, reflection, peer-learning and empowerment. Together, participants will discuss concrete AI tools and workflows, critically assess their opportunities and limitations, and relate current developments to their own doctoral projects and disciplinary contexts.