Sonja Niemann

Sonja Niemann serves as a Scientific Officer Research and research associate at the Bavarian Foundation for Science, Technology and Society (bidt), specializing in human-AI co-creation systems with emphasis on code generation within the pAIrProg research project.

Her academic background includes:

• Bachelor's degree in Psychology from University of Trier
• Master's degree in Computing in the Humanities from Otto-Friedrich University of Bamberg, focusing on cognitive systems and AI

Niemann's research centers on trust dynamics in human-AI collaboration for programming tasks, examining how user expertise levels affect performance outcomes. She actively investigates ethical dimensions of generative AI systems and develops frameworks for equitable human-AI co-creation, integrating cognitive science methodologies with practical AI implementation. Her work bridges technical AI development and human-centered design principles to address real-world adoption challenges.

Her 2025 publication analyzes prompt engineering strategies for optimizing user-AI interactions, demonstrating how structured questioning techniques significantly improve output quality from language models. This research reveals consistent patterns where domain-specific prompt templates outperform generic queries across diverse user skill levels.

As a core contributor to bidt's pAIrProg project, she designs experimental protocols studying human-AI code collaboration. Her public engagement includes co-hosting workshops like 'AI is not neutral – you can change that!' at TINCON 2025, where she demonstrates bias mitigation techniques and advocates for inclusive AI development practices through hands-on coding exercises.