聊天机器人
危害
医学
眼部护理
医学教育
建议(编程)
家庭医学
心理学
眼科
验光服务
人工智能
计算机科学
社会心理学
程序设计语言
作者
Isaac A. Bernstein,Y Zhang,Devendra Govil,Iyad Majid,Robert T. Chang,Yang Sun,Ann Shue,Jonathan Chou,Emily Schehlein,Karen L. Christopher,Sylvia L. Groth,Cassie A. Ludwig,Sophia Y. Wang
出处
期刊:JAMA network open
[American Medical Association]
日期:2023-08-22
卷期号:6 (8): e2330320-e2330320
被引量:230
标识
DOI:10.1001/jamanetworkopen.2023.30320
摘要
In this cross-sectional study of human-written and AI-generated responses to 200 eye care questions from an online advice forum, a chatbot appeared capable of responding to long user-written eye health posts and largely generated appropriate responses that did not differ significantly from ophthalmologist-written responses in terms of incorrect information, likelihood of harm, extent of harm, or deviation from ophthalmologist community standards. Additional research is needed to assess patient attitudes toward LLM-augmented ophthalmologists vs fully autonomous AI content generation, to evaluate clarity and acceptability of LLM-generated answers from the patient perspective, to test the performance of LLMs in a greater variety of clinical contexts, and to determine an optimal manner of utilizing LLMs that is ethical and minimizes harm.
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