This article explores the evolving role of artificial intelligence (AI) as a paternalistic force and its implications for liberal autonomy in the digital age. It reframes AI not merely as a tool or threat, but as a socio-technical agent whose influence emerges through behavioral guidance, manipulation, and decision-making structures. Drawing on philosophical, sociological, and technological perspectives, the paper introduces the concept of liberating paternalism to describe how AI systems subtly reshape human autonomy through voluntary interaction. It identifies four key mechanisms of influence: nudging, manipulation, agency delegation, and ambient governance. Rather than opposing liberal values outright, AI paternalism emerges through widespread reliance on algorithmic systems that structure everyday decisions. This development may signal a potential shift in how autonomy is exercised within liberal societies, raising questions about whether algorithmic governance is gradually reshaping classical liberal assumptions about individual decision-making. Positioned at the intersection of political philosophy and technology ethics, the paper challenges binary framings of freedom and control. It argues that AI-driven paternalism is not imposed but co-constructed, shaped by the user’s needs for well-being, survival, and cognitive ease. In doing so, it highlights the urgency of developing new frameworks that address the ethical, behavioral, and structural dimensions of autonomy in algorithmic societies.

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This article explores the concept of fragile interfaces to examine how electronic literature makes visible the socio-technical infrastructures that shape digital subjectivity. Situated at the intersection of Digital Humanities, media theory, and literary studies, the study addresses a gap in current scholarship by arguing that vulnerability in digital works is not only represented thematically but also embedded in their formal and material conditions. Drawing on N. Katherine Hayles’s notion of the text-interface and Judith Butler’s relational understanding of vulnerability, the article analyzes Alex Saum’s “Room #3” (2020) and J.R. Carpenter’s “Entre Ville” (2006). Through two distinct interface logics (platform simulation and hypertextual urban mapping), these works foreground fragmentation, exposure, and infrastructural dependency. The analysis adopts a qualitative interpretative approach grounded in close reading and rhetorical analysis of digital textual environments, emphasizing the role of interface design, navigational structures, and multimodal composition in the production of meaning. It reveals how digital interfaces structure vulnerability by shaping forms of perception, agency, and relationality, producing fragmented and technologically mediated subjectivities. In this sense, vulnerability emerges not only as thematic content but as a condition enacted through the unstable architectures of digital textuality. By conceptualizing fragility across material, structural, affective, political, and ecological dimensions, this article contributes to ongoing debates in Digital Humanities concerning mediation, platform society, and digital precarity in contemporary cultural production.

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This pilot study explored the potential of relocating English as a Foreign Language (EFL) reading activities to a café setting supported by AI tools. Sixteen intermediate learners (B1–B2) participated in an eight-week, single-group program that combined Google Lens and ChatGPT with peer discussion and instructor guidance. Data were collected through pre/post self-report surveys and guided post-session conversations documented in field notes. The pre-session survey measured enjoyment of reading in English (an affective-motivational construct), whereas the post-session survey measured comfort in the café setting (a situational-environmental construct); these are reported as independent descriptive profiles rather than as a pre-to-post change score. Findings indicated that learners reported high situational comfort in the café environment, sustained engagement across all sessions, and practical benefits from using AI tools for vocabulary support and text clarification. Usability ratings for the tools were moderate, with some participants citing challenges linked to app-switching and cognitive load; two students expressed reservations about environmental distractions and AI tool complexity. The study demonstrates the feasibility and affective appeal of integrating “third-place” learning environments with AI-assisted reading, while acknowledging limitations of sample size, the absence of a control group, reliance on self-report, and the lack of objective comprehension measures. Because the design cannot rule out novelty effects, Hawthorne effects, or social-desirability bias, results should be interpreted as exploratory. These findings suggest that café-based, AI-supported models may enhance learner engagement and merit further controlled research using waitlist-control or crossover designs.

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