AI as Muse or Tool: Preserving Academic Integrity in AI-Augmented Research

​Generative AI is rapidly transforming how researchers search for literature, synthesize knowledge, and draft manuscripts. Yet these systems simulate understanding without possessing it, raising new challenges for academic integrity. This talk explores how scholars can integrate AI tools into their research workflows while maintaining intellectual responsibility and critical judgment.

​Drawing on the framework developed in Truth Matters: Generative AI as Muse or Tool in the Research Process (Birkenkrahe, 2025), the presentation updates the earlier work in light of recent AI developments and the author’s own experiences supervising student research with agentic AI tools.

​The goal is not automation of scholarship, but the development of AI-aware research practices that preserve rigor, transparency, and trust.

​Reference

​Birkenkrahe, M. (2025). Truth Matters: Generative AI as Muse or Tool in the Research Process. International Journal of Electrical and Computer Engineering Research, 5(3), 7–14. https://doi.org/10.53375/ijecer.2025.472

​About Speaker

​Dr. Marcus Birkenkrahe is Professor of Computer and Data Science at Lyon. He holds a PhD in theoretical physics with a focus on lattice gauge theory. His research and teaching span a wide range of areas, including neural networks, multigrid methods, knowledge management, e-learning, literate programming, process modeling, and data science.

​Dr. Birkenkrahe has published extensively across these domains and actively contributes to the academic community as Associate Editor of the International Journal of Data Science. He also serves on the editorial boards of the International Journal of Big Data Management and the International Journal of Learning and Change.