Analysis and news
– in essence, an explanation of the data shown.
While many of the above initiatives
may go unnoticed by most researchers, authors do seem to be experimenting with auto-generated texts. We have seen numerous SciGen-generated manuscripts being submitted to journals and conferences, and academic proofreaders have reported a growing number of requests to ‘post-edit’ texts that have been auto-translated using DeepL[2]
.
Auto-generated or auto-translated text should never be taken at its face value and used ‘as is’. In addition to their lack of scientific understanding, AI-based tools have linguistic limitations, such as the loss of coherence over long texts. Yet, for the time being, they might serve as a useful resource to researchers that struggle with writing, enabling them to discover relevant vocabulary and sentence structures.
Moving towards an all-round AI-based manuscript check? While current NLP initiatives focus on separate pieces of the scientific
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publishing process, in terms of technical capabilities, AI could almost offer all- round manuscript support. Castro adds: ‘In terms of manuscript revision, the needs of authors and publishers align. Publishers increasingly use AI to automate manuscript checks beyond language. For example, does a paragraph refer to the right figure, does the text explain the data accurately, are all citations in the appropriate sentences? These checks are just as useful to authors, and in the future, authors might have them at their disposal too. As they write, they could be getting auto-completions, auto-edits,
“Further uptake of AI-driven proofreading tools can help to reduce the linguistic bias in scientific publishing”
auto-descriptions of their tables, and their references might be verified and automatically populated. And all could be tailored to their journal or discipline.’ While an all-round manuscript check
could make the lives of researchers easier, once they have finalised their paper, the question remains: is the science accurate? In the near future, NLP will likely allow us to produce manuscripts that are fully correct in terms of language, complete and consistent – but evaluating the science will always remain a human task.
Hilde van Zeeland is an applied linguist at Writefull; Juan Castro is CEO and co-founder at Writefull
References
[1] Politzer-Ahles, S., Girolamo, T., & Ghali, S. (2020). Preliminary evidence of linguistic bias in academic reviewing. Journal of English for Academic Purposes, 47.
https://doi.org/10.1016/j. jeap.2020.100895. [2] Textworks Translations. (2019, 16 July). DeepL for academic translations [Blog post]. Retrieved from
https://www.textworks.eu/eng/deepl-for- academic-translations/.
October/November 2021 Research Information
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