Attention is not all you need: the complicated case of ethically using large language models in healthcare and medicine

被引:167
作者
Harrer, Stefan [1 ]
机构
[1] Digital Hlth Cooperat Res Ctr, Melbourne, Vic, Australia
来源
EBIOMEDICINE | 2023年 / 90卷
关键词
Generative arti fi cial intelligence; Large language models; Foundation models; AI ethics; Augmented; human intelligence; Information management; AI trustworthiness;
D O I
10.1016/j.ebiom.2023.104512
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Large Language Models (LLMs) are a key component of generative artificial intelligence (AI) applications for creating new content including text, imagery, audio, code, and videos in response to textual instructions. Without human oversight, guidance and responsible design and operation, such generative AI applications will remain a party trick with substantial potential for creating and spreading misinformation or harmful and inaccurate content at unprecedented scale. However, if positioned and developed responsibly as companions to humans augmenting but not replacing their role in decision making, knowledge retrieval and other cognitive processes, they could evolve into highly efficient, trustworthy, assistive tools for information management. This perspective describes how such tools could transform data management workflows in healthcare and medicine, explains how the underlying technology works, provides an assessment of risks and limitations, and proposes an ethical, technical, and cultural framework for responsible design, development, and deployment. It seeks to incentivise users, developers, providers, and regulators of generative AI that utilises LLMs to collectively prepare for the transformational role this technology could play in evidence-based sectors.
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页数:12
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