TY - JOUR
T1 - Is ChatGPT a “Fire of Prometheus” for Non-Native English-Speaking Researchers in Academic Writing?
AU - Hwang, Sung Il
AU - Lim, Joon Seo
AU - Lee, Ro Woon
AU - Matsui, Yusuke
AU - Iguchi, Toshihiro
AU - Hiraki, Takao
AU - Ahn, Hyungwoo
N1 - Publisher Copyright:
© 2023 The Korean Society of Radiology.
PY - 2023/10
Y1 - 2023/10
N2 - Large language models (LLMs) such as ChatGPT have garnered considerable interest for their potential to aid non-native English-speaking researchers. These models can function as personal, round-the-clock English tutors, akin to how Prometheus in Greek mythology bestowed fire upon humans for their advancement. LLMs can be particularly helpful for non-native researchers in writing the Introduction and Discussion sections of manuscripts, where they often encounter challenges. However, using LLMs to generate text for research manuscripts entails concerns such as hallucination, plagiarism, and privacy issues; to mitigate these risks, authors should verify the accuracy of generated content, employ text similarity detectors, and avoid inputting sensitive information into their prompts. Consequently, it may be more prudent to utilize LLMs for editing and refining text rather than generating large portions of text. Journal policies concerning the use of LLMs vary, but transparency in disclosing artificial intelligence tool usage is emphasized. This paper aims to summarize how LLMs can lower the barrier to academic writing in English, enabling researchers to concentrate on domain-specific research, provided they are used responsibly and cautiously.
AB - Large language models (LLMs) such as ChatGPT have garnered considerable interest for their potential to aid non-native English-speaking researchers. These models can function as personal, round-the-clock English tutors, akin to how Prometheus in Greek mythology bestowed fire upon humans for their advancement. LLMs can be particularly helpful for non-native researchers in writing the Introduction and Discussion sections of manuscripts, where they often encounter challenges. However, using LLMs to generate text for research manuscripts entails concerns such as hallucination, plagiarism, and privacy issues; to mitigate these risks, authors should verify the accuracy of generated content, employ text similarity detectors, and avoid inputting sensitive information into their prompts. Consequently, it may be more prudent to utilize LLMs for editing and refining text rather than generating large portions of text. Journal policies concerning the use of LLMs vary, but transparency in disclosing artificial intelligence tool usage is emphasized. This paper aims to summarize how LLMs can lower the barrier to academic writing in English, enabling researchers to concentrate on domain-specific research, provided they are used responsibly and cautiously.
KW - Academic writing
KW - Artificial intelligence
KW - ChatGPT
KW - Editing
KW - Generative pretrained transformer
KW - Large language model
KW - Publication
UR - http://www.scopus.com/inward/record.url?scp=85173172141&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85173172141&partnerID=8YFLogxK
U2 - 10.3348/kjr.2023.0773
DO - 10.3348/kjr.2023.0773
M3 - Article
C2 - 37793668
AN - SCOPUS:85173172141
SN - 1229-6929
VL - 24
SP - 952
EP - 959
JO - Korean Journal of Radiology
JF - Korean Journal of Radiology
IS - 10
ER -