ChatGPT is likely reducing opportunity for support, friendship and learned kindness in research
Author(s)
Type
Journal Article
Abstract
1. Large language models (LLM) have proved to be highly popular since the releaseof ChatGPT, leading many researchers to explore their potential across multiplefields of scientific research. In a recent Perspective, Cooper et al. (2024) highlighta set of benefits and challenges for the use of LLMs in ecology, emphasising theirvalue to coding in research and education. 2. While we agree that the ability of LLMs to assist in the coding process is remark-able, researchers should be conscious that this capability is likely changing thelived experience of primarily computational researchers, especially early careerecologists between Masters and Postdoctoral career stages. 3. In particular, since the release of ChatGPT, the authors of this paper have noticeda marked reduction in the frequency of social interactions emergent from codingand statistics queries. These questions are highly likely still being asked, but nowoften exclusively to a LLM. 4. Further research is needed to fully understand the effect of LLMs on the lived-experience of researchers and students. For primarily computational research-ers, ChatGPT is likely reducing emergent opportunity for support, friendshipand learned kindness. Group leaders should recognise this and foster deliberatewithin-group communication and collaboration.
Date Issued
2024-10
Online Publication Date
2024-10-03T08:52:38Z
Date Acceptance
2024-06-25
ISSN
2041-210X
Publisher
Wiley
Start Page
1764
End Page
1766
Journal / Book Title
Methods in Ecology and Evolution
Volume
15
Issue
10
Copyright Statement
© 2024 The Author(s). Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
License URI
Identifier
https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.14395
Publication Status
Published
Date Publish Online
2024-10-01