Ethical and Epistemological Dilemmas in Doing Networked Learning Research with AI - Lee, Kyungmee; Bonderup Dohn, Nina; Lacković, Nataša (Proceedings of the International Conference on Networked Learning, 2026)
This round table continues the conversation initiated in the workshop Doing Networked Learning Research with AI, expanding it toward the ethical, relational, and epistemological dilemmas that arise when AI becomes a research collaborator rather than a mere tool. While the workshop focused on how to use generative AI in qualitative research processes—data collection, analysis, and interpretation—this round table invites participants to engage with deeper questions about what it means to do such research responsibly and reflexively. We will discuss how AI’s participation in research assemblages reconfigures human–non-human relations, challenges conventional notions of ethical accountability, and complicates the epistemic boundaries of interpretation. Using Barad’s concept of the agential cut, we will explore how researchers make decisions about what—and who—counts in knowledge production, and what ethical consequences follow from those decisions. Importantly, this session is a standalone discussion: while it directly follows the workshop and extends its themes, participants who did not attend the workshop will be fully able to engage and contribute. The framing and discussion prompts will ensure an inclusive, open entry point for all.