"前无古人":确保人工智能在艾滋病研究分析中的伦理、严谨和深思熟虑应用的问题。

IF 1.6 4区 医学 Q2 NURSING
Alanna J Bergman, Katherine C McNabb, Michael V Relf, Mark H Dredze
{"title":"\"前无古人\":确保人工智能在艾滋病研究分析中的伦理、严谨和深思熟虑应用的问题。","authors":"Alanna J Bergman, Katherine C McNabb, Michael V Relf, Mark H Dredze","doi":"10.1097/JNC.0000000000000483","DOIUrl":null,"url":null,"abstract":"<p><strong>Abstract: </strong>ChatGPT, an artificial intelligence (AI) system released by OpenAI on November 30th, 2022, has upended scientific and educational paradigms, reshaping the way that we think about teaching, writing, and now research. Since that time, qualitative data analytic software programs such as ATLAS.ti have quickly incorporated AI into their programs to assist with or even replace human coding. Qualitative research is key to understanding the complexity and nuance of HIV-related behaviors, through descriptive and historical textual research, as well as the lived experiences of people with HIV. This commentary weighs the pros and cons of the use of AI coding in HIV-related qualitative research. We pose guiding questions that may help researchers evaluate the application and scope of AI in qualitative research as determined by the research question, underlying epistemology, and goal(s). Qualitative data encompasses a variety of media, methodologies, and styles that exist on a spectrum underpinned by epistemology. The research question and the data sources are informed by the researcher's epistemological viewpoint. Given the heterogeneous applications of qualitative research in nursing, medicine, and public health there are circumstances where qualitative AI coding is appropriate, but this should be congruent with the aims and underlying epistemology of the research.</p>","PeriodicalId":50263,"journal":{"name":"Janac-Journal of the Association of Nurses in Aids Care","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11364210/pdf/","citationCount":"0","resultStr":"{\"title\":\"\\\"Where No One Has Gone Before\\\": Questions to Ensure the Ethical, Rigorous, and Thoughtful Application of Artificial Intelligence in the Analysis of HIV Research.\",\"authors\":\"Alanna J Bergman, Katherine C McNabb, Michael V Relf, Mark H Dredze\",\"doi\":\"10.1097/JNC.0000000000000483\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Abstract: </strong>ChatGPT, an artificial intelligence (AI) system released by OpenAI on November 30th, 2022, has upended scientific and educational paradigms, reshaping the way that we think about teaching, writing, and now research. Since that time, qualitative data analytic software programs such as ATLAS.ti have quickly incorporated AI into their programs to assist with or even replace human coding. Qualitative research is key to understanding the complexity and nuance of HIV-related behaviors, through descriptive and historical textual research, as well as the lived experiences of people with HIV. This commentary weighs the pros and cons of the use of AI coding in HIV-related qualitative research. We pose guiding questions that may help researchers evaluate the application and scope of AI in qualitative research as determined by the research question, underlying epistemology, and goal(s). Qualitative data encompasses a variety of media, methodologies, and styles that exist on a spectrum underpinned by epistemology. The research question and the data sources are informed by the researcher's epistemological viewpoint. Given the heterogeneous applications of qualitative research in nursing, medicine, and public health there are circumstances where qualitative AI coding is appropriate, but this should be congruent with the aims and underlying epistemology of the research.</p>\",\"PeriodicalId\":50263,\"journal\":{\"name\":\"Janac-Journal of the Association of Nurses in Aids Care\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11364210/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Janac-Journal of the Association of Nurses in Aids Care\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/JNC.0000000000000483\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/8/6 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"NURSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Janac-Journal of the Association of Nurses in Aids Care","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/JNC.0000000000000483","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/8/6 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"NURSING","Score":null,"Total":0}
引用次数: 0

摘要

摘要:ChatGPT 是 OpenAI 于 2022 年 11 月 30 日发布的人工智能(AI)系统,它颠覆了科学和教育范式,重塑了我们对教学、写作和研究的思维方式。从那时起,ATLAS.ti 等定性数据分析软件程序已迅速将人工智能纳入其程序,以协助甚至取代人工编码。定性研究是通过描述性和历史性文本研究以及 HIV 感染者的生活经历来了解 HIV 相关行为的复杂性和细微差别的关键。本评论权衡了在 HIV 相关定性研究中使用人工智能编码的利弊。我们提出了一些指导性问题,可以帮助研究人员根据研究问题、基本认识论和目标来评估人工智能在定性研究中的应用和范围。定性数据包括各种媒介、方法和风格,它们存在于以认识论为基础的光谱上。研究者的认识论观点决定了研究问题和数据来源。鉴于定性研究在护理、医学和公共卫生领域的应用多种多样,在某些情况下,定性人工智能编码是合适的,但这应与研究的目的和基本认识论相一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
"Where No One Has Gone Before": Questions to Ensure the Ethical, Rigorous, and Thoughtful Application of Artificial Intelligence in the Analysis of HIV Research.

Abstract: ChatGPT, an artificial intelligence (AI) system released by OpenAI on November 30th, 2022, has upended scientific and educational paradigms, reshaping the way that we think about teaching, writing, and now research. Since that time, qualitative data analytic software programs such as ATLAS.ti have quickly incorporated AI into their programs to assist with or even replace human coding. Qualitative research is key to understanding the complexity and nuance of HIV-related behaviors, through descriptive and historical textual research, as well as the lived experiences of people with HIV. This commentary weighs the pros and cons of the use of AI coding in HIV-related qualitative research. We pose guiding questions that may help researchers evaluate the application and scope of AI in qualitative research as determined by the research question, underlying epistemology, and goal(s). Qualitative data encompasses a variety of media, methodologies, and styles that exist on a spectrum underpinned by epistemology. The research question and the data sources are informed by the researcher's epistemological viewpoint. Given the heterogeneous applications of qualitative research in nursing, medicine, and public health there are circumstances where qualitative AI coding is appropriate, but this should be congruent with the aims and underlying epistemology of the research.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
2.90
自引率
10.00%
发文量
120
期刊介绍: The Journal of the Association of Nurses in AIDS Care (JANAC) is a peer-reviewed, international nursing journal that covers the full spectrum of the global HIV epidemic, focusing on prevention, evidence-based care management, interprofessional clinical care, research, advocacy, policy, education, social determinants of health, epidemiology, and program development. JANAC functions according to the highest standards of ethical publishing practices and offers innovative publication options, including Open Access and prepublication article posting, where the journal can post articles before they are published with an issue.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信