Data Snack - Beyond ChatGPT: AI Systems for Qualitative Research

Qualitative research enables the in-depth exploration of social phenomena and the complexity of human interactions. Non-numerical data is created – often in the form of interviews, observation protocols, or visual materials. However, both data preparation, such as transcribing audio files, and data analysis prove to be extraordinarily time-intensive.

In the digital age, qualitative researchers with programming backgrounds are increasingly developing innovative software solutions to support their colleagues in these labor-intensive processes. The integration of AI-supported tools into qualitative research thereby leads to important controversial discussions within the research community.

While epistemological debates about the impact of digital methods on the research process remain essential, this Data Snack focuses on concrete tools that are based on AI models or incorporate them for support. The aim of this session is to highlight possibilities that exist beyond ChatGPT. While the open-source nature of these tools allows for code review and modification, researchers remain responsible for implementing appropriate data protection measures, evaluating algorithmic bias, and maintaining methodological transparency in AI-assisted analysis workflows.