Open education's foundational promise is access. But access to a system that normalizes particular ways of knowing is not equity; it is assimilation. As AI tools enter open education, they inherit and amplify this problem: adaptive learning systems, AI writing assistants, and OER generation tools are trained on dominant epistemological frameworks and optimize toward measurable outcomes. Queer pedagogy offers a different orientation: valuing friction, centering non-normative knowledge formations, and refusing the smoothing work of optimization. This session introduces queerness as a practical framework for AI use in open education and draws on Bernard Stiegler's concept of the pharmakon to argue that AI in open ed is both remedy and poison. Attendees will leave with concrete strategies for designing AI encounters that interrogate what counts as knowledge, who AI is built for, and how to treat productive friction as pedagogy rather than a problem to fix.
Attendees of this session will be able to:- Outcome 1: identify how AI tools deployed in open educational contexts normalize particular knowledge formations and marginalize others.
- Outcome 2: recognize moments in their own practice where AI smooths over productive friction that should be preserved pedagogically.
- Outcome 3: apply a queer pedagogical framework to redesign at least one AI encounter in their courses so that students engage friction critically rather than resolve it.
