Large Language Models and the future of scientific publishing
DIPF Frankfurt
Join our workshop to explore the chances and challenges Large Language Models pose for scientific writing and academic journals.
Interact with researchers, publishers, and start-ups to navigate the evolving landscape together!
Large Language Models (LLMs) have already started to severely impact scientific workflows. Their influence is set to grow even further and at speeds that exceed previous transformational changes. LLMs will most visibly affect a most central element of science: publications. They will decrease the burden of creating scientific articles which are the culmination of research data production. Tools are already under development (e.g. Paperpal) that decrease the duration of creating the first draft. LLMs therefore melt down the time from data collection to publication. These software developments will help reap the benefits of research data in a timely fashion but will ultimately also result in an increase of journal submissions. Existing quality assurance mechanisms (esp. peer review) will therefore be challenged both in terms of volume but also in term of the criteria to assess the value-added of publications.
This workshop will bring together researchers and publishing houses to identify and address the challenges for the journals as well as the increased demands of the reviewers and the wider research community. Furthermore, the workshop should identify possible chances by using LLM technologies within the publishing process and open the path for future discussions on this topic. Thereby, we accelerate the exchange and harmonization of user-journeys for future publications.
"Since 2023, it became much more difficult to find work as an academic copy editor compared with the previous 10 years. This coincides with the widespread use of ChatGPT. As a result, I had to find a new occupation." SK (North-american academic copy editor)
- NFDI-MatWerk
- S. Brinckmann (FZ-Jülich), J. Mohrbacher (Uni Freiburg)
- KonsortSWD
- B. Miller (GESIS), Sonja Bayer (DIPF)
- NFDI4Chem
- F. Eberl (Uni Jena), N. Parks (RWTH)
- NFDI4Earth
- A. Degbelo (TU Dresden), C. Schmidt (GFZ)
- Text+
- T. Trippel (IDS Mannheim)
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