公共卫生中负责任的人工智能:关于风险沟通、社区参与和信息管理的德尔菲研究。

IF 7.1 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Daniela Mahl, Mike S Schäfer, Stefan Adrian Voinea, Keyrellous Adib, Ben Duncan, Cristiana Salvi, David Novillo-Ortiz
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引用次数: 0

摘要

导语:人工智能(AI)有可能从根本上改变公共卫生当局如何利用风险沟通、社区参与和信息管理(rce - im)来准备、管理和减轻突发公共卫生事件。由于对这一关键转变的研究仍然有限,我们对人工智能对rce - im的影响进行了修正的德尔菲研究。方法:在两次连续调查中,来自27个国家的54名专家-具有公共卫生、数字卫生、卫生传播、风险沟通和人工智能专业知识的学者以及rce - im专业人员-评估了人工智能的机遇、挑战和风险,预测了未来的情景,并确定了促进负责任地使用人工智能的原则和行动。第一轮德尔福融资采用了一种开放的、探索性的方法,而第二轮则寻求对初始阶段的关键发现进行优先排序和排名。定性专题分析和统计方法应用于评价反应。结果:根据专家小组的说法,人工智能可能非常有益,特别是在风险沟通(例如,定制信息)和信息管理(例如,社交倾听)方面,而它在促进社区参与方面的效用则更为重要。挑战和风险同样影响着rce - im的所有三个组成部分,算法偏见和隐私泄露尤其令人担忧。小组成员预测了乐观(例如,信息民主化)和悲观(例如,公众信任的侵蚀)的未来情景。他们确定了负责任地在公共卫生实践中使用人工智能的七项原则,其中公平和透明是最重要的。优先行动范围从监管措施、资源分配和反馈循环到能力建设、公众信任倡议和教育培训。结论:为了负责任地应对突发公共卫生事件中rce - im人工智能带来的多方面机遇、挑战和风险,需要明确的指导原则、持续的关键评估和培训以及各国之间的社会合作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Responsible artificial intelligence in public health: a Delphi study on risk communication, community engagement and infodemic management.

Introduction: Artificial intelligence (AI) holds the potential to fundamentally transform how public health authorities use risk communication, community engagement and infodemic management (RCCE-IM) to prepare for, manage and mitigate public health emergencies. As research on this crucial transformation remains limited, we conducted a modified Delphi study on the impact of AI on RCCE-IM.

Methods: In two successive surveys, 54 experts-scholars with expertise in public health, digital health, health communication, risk communication and AI, as well as RCCE-IM professionals-from 27 countries assessed opportunities, challenges and risks of AI, anticipated future scenarios, and identified principles and actions to facilitate the responsible use of AI. The first Delphi round followed an open, exploratory approach, while the second sought to prioritise and rank key findings from the initial phase. Qualitative thematic analysis and statistical methods were applied to evaluate responses.

Results: According to the expert panel, AI could be highly beneficial, particularly for risk communication (eg, tailoring messages) and infodemic management (eg, social listening), while its utility for fostering community engagement was viewed more critically. Challenges and risks affect all three components of RCCE-IM equally, with algorithmic bias and privacy breaches being of particular concern. Panellists anticipated both optimistic (eg, democratisation of information) and pessimistic (eg, erosion of public trust) future scenarios. They identified seven principles for the responsible use of AI for public health practices, with equity and transparency being the most important. Prioritised actions ranged from regulatory measures, resource allocation and feedback loops to capacity building, public trust initiatives and educational training.

Conclusion: To responsibly navigate the multifaceted opportunities, challenges and risks of AI for RCCE-IM in public health emergencies, clear guiding principles, ongoing critical evaluation and training as well as societal collaboration across countries are needed.

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来源期刊
BMJ Global Health
BMJ Global Health Medicine-Health Policy
CiteScore
11.40
自引率
4.90%
发文量
429
审稿时长
18 weeks
期刊介绍: BMJ Global Health is an online Open Access journal from BMJ that focuses on publishing high-quality peer-reviewed content pertinent to individuals engaged in global health, including policy makers, funders, researchers, clinicians, and frontline healthcare workers. The journal encompasses all facets of global health, with a special emphasis on submissions addressing underfunded areas such as non-communicable diseases (NCDs). It welcomes research across all study phases and designs, from study protocols to phase I trials to meta-analyses, including small or specialized studies. The journal also encourages opinionated discussions on controversial topics.
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