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Short abstract

We present the structure, techniques, and results of three variations of our use of a critical AI literacy methodology, a guided autoethnographic DIY toolkit where students produce field diaries analyzing their relationships with genAI, generating deep reflection, critique, and future imaginaries.

Long abstract

In recent years, genAI systems have emerged as key, intimate actors in the granular processes of interaction in which socio-cultural relations are shaped, individuals are constituted as subjects and meaning-making activities and identity-formation processes emerge. This has brought considerable new attention to the importance of critical literacies about genAI and emerging machinic capabilities within complex ecosystems of interdependent human and non-human activities (Markham and Pronzato, 2023; Pangrazio, 2026).

However, in this scenario, sustained literacy is difficult to achieve: individuals confront computational systems that are extremely difficult to comprehend, with interfaces designed to encourage continuous use and illusion of control (Pronzato and Markham, 2023), while Big Tech’s enormous power and persuasive narratives normalise techno-determinist futures as inevitable (Markham, 2021).

We present three applications of Markham’s 2012 guided autoethnographic methodology: a three-day, a two-week, and a 21-day version, where facilitators train students to study their own relations with AI. Beyond focusing on how they or other students define, use, and feel about GenAI currently, they consider how current trends are influencing the future of higher education. This guided autoethnography method ー grounded in interpretative and narrative inquiry, critical pedagogy, technofeminism, and critical theory ー is useful for understanding student’s experiences, but more, fosters self-reflexivity, critical examination of how AI seeps into everyday life, and activates critical consciousness that is deeply personal, foundational to strengthening critical AI literacies. The project involves IULM University, Queensland University of Technology, and Utrecht University, and is part of the work of the Futures+ Literacies+ Methods Lab (FLL).