Generative Machine-Learning-Systeme verändern das wissenschaftliche Schreiben
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Bemerkungen
Of the ERC survey respondents, 85% thought that generative AI could take on repetitive or labour-intensive tasks, such as literature reviews. And 38% felt that generative AI would promote productivity in science, such as by helping researchers to write papers at a faster pace.
Von McKenzie Prillaman im Text Is ChatGPT making scientists hyper-productive? (2024) And there is a drawback to the productivity boost that LLMs might bring. Speeding up the paper-writing process could increase throughput at journals, potentially stretching editors and peer reviewers even thinner than they already are. “With this ever-increasing number of papers — because the numbers are going up every year — there just aren’t enough people available to continue to do free peer review for publishers,” Lancaster says.
Von McKenzie Prillaman im Text Is ChatGPT making scientists hyper-productive? (2024) About 55% of the respondents to the Nature survey felt that a major benefit of generative AI is its ability to edit and translate writing for researchers whose first language is not English. Similarly, in a poll by the European Research Council (ERC), which funds research in the European Union, 75% of more than 1,000 ERC grant recipients felt that generative AI would reduce language barriers in research by 2030, according to a report released in December
Von McKenzie Prillaman im Text Is ChatGPT making scientists hyper-productive? (2024) Zitationsgraph
5 Erwähnungen
- Wie wir in Zukunft wissenschaftliche Texte schreiben (könnten) - Teil 3 (Noah Bubenhofer) (2023)
- Hausaufgaben machen mit ChatGPT? (Heike Schmoll) (2023)
- Wie wir in Zukunft wissenschaftliche Texte schreiben (könnten) - Teil 2 (Noah Bubenhofer) (2023)
- 9 Mythen über generative KI in der Hochschulbildung (Julius-David Friedrich, Jens Tobor, Martin Won) (2024)
- Is ChatGPT making scientists hyper-productive? - The highs and lows of using AI (McKenzie Prillaman) (2024)