Romanticising the algorithm: power dynamics and ideological implications in human–AI collaboration for higher education

Abstract This article examines how undergraduate students appropriate generative AI within higher education, focussing on how their practices both reproduce and contest prevailing algorithmic and neoliberal logics. Drawing on 40 reflexive diaries produced by 186 students enrolled in a journalism course, the study employs thematic coding to analyse how AI tools were integrated into collective production processes such as brainstorming, drafting, and editing, and how students reflected on the benefits, limitations, and ethical implications of these uses. The analysis identifies four distinct profiles of AI use: selective optimisers (targeted, efficiency-oriented use), critical experimenters (reflective and exploratory use with supervision margins), exploratory users (creative and uncertain engagement), and tech functional (minimal and technical use). These profiles reveal how students negotiated AI’s potential to enhance efficiency and creativity while simultaneously raising concerns about accuracy, reliability, and academic integrity. The findings suggest that students do not adopt AI uncritically but situate its use within broader negotiations over competence, authorship, and legitimacy. AI is perceived as a supportive but non-substitutive partner, requiring continuous human oversight and reflexive engagement. The results underscore the tension between instrumental benefits, such as time-saving, and deeper pedagogical questions concerning responsibility, agency, and the redistribution of academic labour. By highlighting the ambivalences and situated practices of AI appropriation, the article contributes to critical debates on the role of generative AI in higher education, pointing to the need for pedagogical frameworks that balance efficiency with reflexivity and safeguard human decision-making in contexts increasingly shaped by algorithmic technologies.