The transformation of the category of authorship in the context of the widespread use of generative neural networks is manifested in the rethinking of the criteria that define the boundaries between human and algorithmically generated text at the intersection of linguistic, cultural, and institutional dimensions. Reader's interpretations consistently contrast machine writing, characterized by formulaic language, lexical repetition, syntactic rigidity, emotional flatness, and lack of intentionality, with the features of human discourse, including stylistic uniqueness, idiosyncratic deviations, unexpected metaphors, emotional unevenness, references to personal experiences, and a sense of conscious responsibility for the message. However, there are internal contradictions, where both excessive polish and the presence of semantic or grammatical deviations can signal artificiality, depending on genre conventions and cultural attitudes. The official positions of publishing and scientific institutions emphasize the inseparable connection between authorship and ethical responsibility, as well as the ability to make conscious language choices, excluding the possibility of recognizing neural networks as authors or co-authors, which is reflected in the mandatory declaration policies for the use of artificial intelligence. At the same time, the protest practices of the writing community are developing, aimed against the unauthorized use of literary works for training models, which is most clearly expressed in collective manifestations that involve the symbolic denial of the value of content created without respect for the rights of its creators. The publishing environment, in turn, demonstrates the pragmatic integration of neural network tools for risk analytics, the generation of supporting materials, and the optimization of workflows, while maintaining human control over the final product and the author's status. The integration of these perspectives allows for the development of editorial approaches focused on identifying the naturalness of speech through the analysis of linguistic markers of individuality, ensuring the transparency of technology use without creating stigmatizing effects, and flexibly regulating contractual relationships based on the level of algorithmic involvement, which contributes to maintaining the communicative value of texts and audience trust. This comprehensive approach highlights the culturally-specific nature of the author's function, its evolution in the digital environment, and the need for humanitarian reflection based on philosophical traditions of understanding reading and discursive practices to develop adaptive strategies in pedagogical, publishing, and educational contexts, thereby providing a foundation for informed decision-making regarding the relevance of materials in automated information retrieval systems.