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“人工智能将对社会中的一切产生影响,因此它必然会对公共卫生产生影响”:一项关于人工智能对公共卫生影响的基本定性描述性研究。

"AI's gonna have an impact on everything in society, so it has to have an impact on public health": a fundamental qualitative descriptive study of the implications of artificial intelligence for public health.

作者信息

Morgenstern Jason D, Rosella Laura C, Daley Mark J, Goel Vivek, Schünemann Holger J, Piggott Thomas

机构信息

Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada.

Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.

出版信息

BMC Public Health. 2021 Jan 6;21(1):40. doi: 10.1186/s12889-020-10030-x.

DOI:10.1186/s12889-020-10030-x
PMID:33407254
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7787411/
Abstract

BACKGROUND

Our objective was to determine the impacts of artificial intelligence (AI) on public health practice.

METHODS

We used a fundamental qualitative descriptive study design, enrolling 15 experts in public health and AI from June 2018 until July 2019 who worked in North America and Asia. We conducted in-depth semi-structured interviews, iteratively coded the resulting transcripts, and analyzed the results thematically.

RESULTS

We developed 137 codes, from which nine themes emerged. The themes included opportunities such as leveraging big data and improving interventions; barriers to adoption such as confusion regarding AI's applicability, limited capacity, and poor data quality; and risks such as propagation of bias, exacerbation of inequity, hype, and poor regulation.

CONCLUSIONS

Experts are cautiously optimistic about AI's impacts on public health practice, particularly for improving disease surveillance. However, they perceived substantial barriers, such as a lack of available expertise, and risks, including inadequate regulation. Therefore, investment and research into AI for public health practice would likely be beneficial. However, increased access to high-quality data, research and education regarding the limitations of AI, and development of rigorous regulation are necessary to realize these benefits.

摘要

背景

我们的目标是确定人工智能(AI)对公共卫生实践的影响。

方法

我们采用了基本的定性描述性研究设计,在2018年6月至2019年7月期间招募了15位来自北美和亚洲从事公共卫生与人工智能工作的专家。我们进行了深入的半结构化访谈,对访谈记录进行迭代编码,并对结果进行主题分析。

结果

我们生成了137个代码,从中提炼出九个主题。这些主题包括利用大数据和改进干预措施等机遇;人工智能适用性认知混乱、能力有限和数据质量差等采用障碍;以及偏差传播、不平等加剧、炒作和监管不力等风险。

结论

专家们对人工智能对公共卫生实践的影响持谨慎乐观态度,特别是在改善疾病监测方面。然而,他们意识到了重大障碍,如缺乏可用的专业知识,以及包括监管不足在内的风险。因此,对用于公共卫生实践的人工智能进行投资和研究可能会有所裨益。然而,要实现这些益处,必须增加高质量数据的获取、开展关于人工智能局限性的研究和教育,并制定严格的监管措施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63a9/7788788/a677053f53f0/12889_2020_10030_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63a9/7788788/a677053f53f0/12889_2020_10030_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/63a9/7788788/a677053f53f0/12889_2020_10030_Fig1_HTML.jpg

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