Details

Autor(en) / Beteiligte

• Meyer, Jesse G
• Urbanowicz, Ryan J
• Martin, Patrick C N
• O'Connor, Karen
• Li, Ruowang
• Peng, Pei-Chen
• Bright, Tiffani J
• Tatonetti, Nicholas
• Won, Kyoung Jae
• Gonzalez-Hernandez, Graciela
• Moore, Jason H

Titel

ChatGPT and large language models in academia: opportunities and challenges

Ist Teil von

• BioData mining, 2023-07, Vol.16 (1), p.20-20, Article 20

Ort / Verlag

England: BioMed Central Ltd

Erscheinungsjahr

2023

Link zum Volltext

Quelle

Free E-Journal (出版社公開部分のみ）

Beschreibungen/Notizen

• 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.