AI-Supported Knowledge Synthesis
knowledge synthesis, literature reviews, artificial intelligence
Thesis Advisor: Prof. Dr. Gerit Wagner
Summary: In this topic area, we investigate how AI can support knowledge synthesis across academic and professional contexts. The focus is on improving transparency, rigor, traceability, and sensemaking in AI-assisted synthesis processes. Topics may include the design and evaluation of prompts for structured synthesis, classification of AI use in knowledge work outputs, benchmarking AI-supported synthesis workflows, and the development of infrastructures that make AI contributions auditable and reusable. This area explicitly includes literature reviews as well as knowledge synthesis in digital gardens, second-brain systems, and other personal or organizational knowledge repositories. The overarching aim is to understand and shape how AI supports the production, integration, and validation of knowledge.
Methods: Literature reviews, design science research, or case studies.
References:
Clark J, Barton B, Albarqouni L, et al. Generative artificial intelligence use in evidence synthesis: A systematic review. Research Synthesis Methods. 2025;16(4):601-619. doi:10.1017/rsm.2025.16
Wagner, G., Lukyanenko, R., & Paré, G. (2022). Artificial intelligence and the conduct of literature reviews. Journal of Information Technology, 37(2), 209-226.