When the machine writes back: generative AI, literary agency, and the reconfiguration of digital authorship - Aisultanova Karlygash Abdukalykowna; Syaiful Islam (Asosiasi Relawan dan Pengelola Jurnal LPTNU (ARJUNU), 2026)
Background: Generative artificial intelligence has destabilized conventional literary authorship by separating textual production from ownership, responsibility, and institutional recognition across digital publishing environments. Objective: This study examines how human writers, generative systems, editors, publishers, platforms, and cultural institutions redistribute literary agency, attribution, disclosure, and legitimacy. Method: Using a qualitative comparative corpus design, this study analyzed 42 public documents published between 2021 and 11 July 2026, comprising 15 primary, 13 secondary, and 14 contextual sources through distributed-authorship mapping, workflow-chain analysis, and paratextual governance analysis. Results: Human actors retained legal, editorial, and ethical primacy, although machines increasingly occupied visible roles in drafting, stylistic production, and symbolic co-authorship. Literary agency operated across prompting, generation, selection, revision, arrangement, performance, and publication rather than residing exclusively in sentence production. Disclosure functioned constitutively, legitimizing experimentation in some contexts while enabling suspicion, restriction, or prohibition in others. Implication: Digital authorship should therefore be evaluated as a governed attribution network in which distributed creativity remains asymmetrical because accountability continues to rest with identifiable human and institutional actors. Novelty: This study integrates literary texts, creator accounts, publisher paratexts, media reception, platform rules, and policy documents within one auditable framework connecting attribution, workflow, and governance across contemporary transnational literary ecosystems.