The DZHW Working Group on Automation and AI in Academic Publishing examines the growing role of digital technologies and AI in reshaping scholarly communication. Digital tools are becoming integral to many aspects of academic publishing, from data collection and analysis to manuscript preparation and writing, from integrity screening to peer review and editorial decision-making, and from searching for and finding literature to reading, summarizing, and citing papers. While these technologies promise to reduce workloads and enhance objectivity, they also raise concerns about bias, transparency, and the role of human expertise in reconfiguring traditional publishing processes.
For example, Editorial Management Systems (EMS), plagiarism detection software, and automated tools for suggesting reviewers and citations are now widely used in academic publishing. These tools shift the distribution of tasks, affecting how manuscripts are reviewed and who participates in the peer review process. Moreover, as generative AI tools such as ChatGPT continue to develop, their use in drafting research articles and analyzing data introduces further complexities, raising questions about the reliability and ethical implications of AI-generated content. As AI-driven systems enable dynamic, on-demand outputs that cater to individual reader preferences, traditional static publications may become obsolete. As such, these developments also fundamentally challenge existing evaluation frameworks tied to individual research papers, journal prestige and further publication metrics. As such, we can witness the effects of the digital transformation both at the individual level (e.g., individual writing and reviewing practices), the meso-level (e.g., at journals and publishing houses), as well as at the macro-level (the overall structure of the publishing system).
The working group considers the future of academic publishing in light of these changes. It provides a forum for researchers at the DZHW to bring together research strands, questions and data collected in existing projects. Through regular discussions, it aims to identify overlap between individual projects and research approaches, and to generate new ideas and research projects that critically assess the role of these technologies.
The working group focuses on questions such as:
- How do AI tools in publishing impact the distribution of labor and authority in academic publishing?
- What biases and ethical concerns arise from the use of AI in academic publishing?
- Which new publication formats and publishing processes might emerge through the digital transformation?
- What new evaluative frameworks are needed to assess quality and impact in an AI-driven publishing ecosystem?
- How can data quality be ensured in the use of AI tools in the scientific publishing process to guarantee the reliability and validity of the generated content?
