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ChatGPT and large language models in academia: opportunities and challenges

Authors :
Jesse G. Meyer
Ryan J. Urbanowicz
Patrick C. N. Martin
Karen O’Connor
Ruowang Li
Pei-Chen Peng
Tiffani J. Bright
Nicholas Tatonetti
Kyoung Jae Won
Graciela Gonzalez-Hernandez
Jason H. Moore
Source :
BioData Mining, Vol 16, Iss 1, Pp 1-11 (2023)
Publication Year :
2023
Publisher :
BMC, 2023.

Abstract

Abstract The introduction of large language models (LLMs) that allow iterative “chat” in late 2022 is a paradigm shift that enables generation of text often indistinguishable from that written by humans. LLM-based chatbots have immense potential to improve academic work efficiency, but the ethical implications of their fair use and inherent bias must be considered. In this editorial, we discuss this technology from the academic’s perspective with regard to its limitations and utility for academic writing, education, and programming. We end with our stance with regard to using LLMs and chatbots in academia, which is summarized as (1) we must find ways to effectively use them, (2) their use does not constitute plagiarism (although they may produce plagiarized text), (3) we must quantify their bias, (4) users must be cautious of their poor accuracy, and (5) the future is bright for their application to research and as an academic tool.

Details

Language :
English
ISSN :
17560381
Volume :
16
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BioData Mining
Publication Type :
Academic Journal
Accession number :
edsdoj.4064623157dd4394a531c1a35468a3a1
Document Type :
article
Full Text :
https://doi.org/10.1186/s13040-023-00339-9