ChatGPT as an assistant for digital scholarly editing

Large language models such as OpenAI’s ChatGPT have rapidly become prominent tools in academic contexts, including digital scholarly editing. Although not originally designed for editorial practice, they are increasingly integrated into experimental editorial workflows. This review assesses its potential to support key editorial tasks and surveys recent literature on their use in digital scholarly editing. Drawing on published case studies and our own experiments, we analyze the benefits and limitations of employing ChatGPT at different stages of creating and analyzing digital scholarly editions, including transcription, TEI encoding, and named-entity recognition. At the same time, the review addresses significant concerns. As a commercial and largely closed system, ChatGPT operates as a ‘black box’ that allows only indirect control through prompting, raising challenges for transparency and reproducibility in academic contexts. Issues of model bias and data governance must be carefully considered when integrating such tools into research workflows. ChatGPT should therefore be adopted cautiously and critically. Nevertheless, its capacity to lower technical barriers and to consolidate tasks that previously required multiple tools and advanced programming skills makes it, or similar artificial intelligence tools, a potentially valuable assistant in digital editing workflows.