Seeing Myself in Pixels: Autoethnographic Reflections with GenAI on the Stories We Fight To Keep

This essay explores the integration of generative artificial intelligence (GenAI) as a co-creative partner in autoethnographic research and teaching, focusing on the production of creative artefacts as evidence. Centring on my use of GenAI to create two representative images of my academic identity as both educator and researcher, I reflect on the iterative and dialogic process of prompting, interpretation, and refinement that characterised this visual inquiry. These images, initially intended to be published in a book chapter on GenAI, served not only as evocative representations but also as catalysts for deep self-reflection and theoretical exploration. Despite the profound insights I gained through this visual journey, the figures which were so central to my sense-making were ultimately silenced by the gatekeeping logic of existing publication norms. Denied a place in the formal publication, I gave the images life elsewhere through an open-access repository and cited them in the final published chapter. In this way, I used the academic citation norms as a subtle defiance, a deliberate move against the constraints that sought to erase part of my scholarly voice. I have since extended this innovation into the classroom, developing a pedagogical approach where students use GenAI to visualise and narrate aspects of their own identities in their own autoethnographic projects. This essay illuminates both the empowering possibilities and institutional barriers encountered when introducing novel modes of research sharing. By foregrounding visual evidence co-created with GenAI, this work advocates for more inclusive, imaginative, and multimodal approaches to academic expression.