ChatGPT and generative AI are revolutionizing the scientific community: A Janus‐faced conundrum
Zhong Ji Pu, Chun‐Lin Shi, Che Ok Jeon, Jingyuan Fu, Shuang‐Jiang Liu, Canhui Lan, Yanlai Yao, Yongxin Liu and 1 more
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AChecked 1 Oct 2026. Open license (CC-BY, CC-BY-SA, CC0, public domain): full text indexed and used in synthesis.
| Source | License | Open-access status | Read as |
|---|---|---|---|
| openalex | cc-by | gold | Green |
| crossref | http://creativecommons.org/licenses/by/4.0/ | — | Green |
| unpaywall | cc-by | gold | Green |
| europepmc | cc by | — | Green |
Abstract
BThe advent of generative artificial intelligence (AI) technologies marks a transformative moment for the scientific sphere, unlocking novel avenues to elevate scientific writing's efficiency and quality, expedite insight discovery, and enhance code development processes. Essential to leveraging these advancements is prompt engineering, a method that enhances AI interaction efficiency and quality. Despite its benefits, effective application requires blending researchers' expertise with AI, avoiding overreliance. A balanced strategy of integrating AI with independent critical thinking ensures the advancement and quality of scientific research, leveraging innovation while maintaining research integrity.
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