Year: 2025
Type: dissertation
Abstract: This master’s thesis examines the impact of large language models (LLMs) on the editorial process of literary fiction. Through a literature review, the study outlines the stages of the editorial workflow and evaluates how AI-based language models can be utilized for automation, as well as how this technology influences the editorial process. The findings indicate that LLM technology already performs well in mechanical tasks such as technical proofreading, stylistic refinement, and metadata classification – even surpassing human accuracy in some cases – which can significantly accelerate these stages. However, challenges arise when LLMs are applied to tasks requiring creative thinking, preserving the author’s voice, and strategically targeting the work. The study proposes a hybrid architecture in which an AI agent utilizes appropriate LLM and RPA tools for each stage of the process, making either confirmable suggestions or direct changes depending on the context. The research also ad-dresses ethical and legal challenges, such as copyright issues, bias detection, and the need for transparent collaboration among authors, editors, and publishers. The results suggest that the use of LLM-based technology in the publishing industry is increasing, but human editors remain essential as active contributors and curators of content, whose professional experience and inter-personal skills are irreplaceable in creative work. In this way, the artistic quality of literature can be safeguarded while benefiting from the efficiency brought by LLM solutions.
Source: Aaltodoc (Aalto University)
Author: Tuominen, Topias
Language: English
Subfield: Library and Information Sciences
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7076968859