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Paper short abstract

How autoethnographic diaries can make visible what GenAI forecloses: findings from an action-research study involving 270 Italian university students reveal the realities strengthened and hindered by everyday AI use.

Paper long abstract

The ongoing hype around Artificial Intelligence continues to produce enchanted narratives about AI's capabilities and societal relevance (Campolo & Crawford, 2021), while critics point to hallucinations, bias reproduction, and the limits of technical explainability (Argyle et al., 2023; Bassett & Roberts, 2023). Within this contested landscape, understanding how individuals actually appropriate GenAI in situated practices remains an empirical and theoretical challenge for STS scholars. This contribution asks: what kinds of representations of 'the social' emerge through everyday GenAI use, and what realities are made visible—or foreclosed—when AI becomes embedded in knowledge-making practices?

We present a two-week guided autoethnographic diary deployed in an action-research study involving 270 Italian university students, developed in collaboration with the FLL at Utrecht University. Grounded in interpretative inquiry, critical theory and STS studies, the diary investigates AI situated practice from within everyday use, questioning its 'thingness' (Suchman, 2023) at the intersection of GenAI, technological solutionism (Macgilchrist et al., 2025), and power asymmetries in human-machine relations (Couldry & Mejias, 2019), making the academy a privileged site for observing how AI becomes accommodated within institutional knowledge-making.

Findings show how diary-based approaches elicit granular, situated accounts that aggregate data cannot capture (Di Fraia & Risi, 2017)—revealing opacity, contradictions, and affective dimensions of GenAI use, and making visible what remains hidden within black-boxed systems (Pangrazio & Selwyn, 2023). We argue that autoethnographic methods offer STS scholarship a productive empirical toolkit to investigate the social imaginaries co-produced through human-AI interaction, and the realities strengthened or hindered when GenAI enters knowledge production.