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支持公共卫生通信的通用对话式人工智能时代。

Era of Generalist Conversational Artificial Intelligence to Support Public Health Communications.

作者信息

Sezgin Emre, Kocaballi Ahmet Baki

机构信息

The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, United States.

College of Medicine, The Ohio State University, Columbus, OH, United States.

出版信息

J Med Internet Res. 2025 Jan 20;27:e69007. doi: 10.2196/69007.

Abstract

The integration of artificial intelligence (AI) into health communication systems has introduced a transformative approach to public health management, particularly during public health emergencies, capable of reaching billions through familiar digital channels. This paper explores the utility and implications of generalist conversational artificial intelligence (CAI) advanced AI systems trained on extensive datasets to handle a wide range of conversational tasks across various domains with human-like responsiveness. The specific focus is on the application of generalist CAI within messaging services, emphasizing its potential to enhance public health communication. We highlight the evolution and current applications of AI-driven messaging services, including their ability to provide personalized, scalable, and accessible health interventions. Specifically, we discuss the integration of large language models and generative AI in mainstream messaging platforms, which potentially outperform traditional information retrieval systems in public health contexts. We report a critical examination of the advantages of generalist CAI in delivering health information, with a case of its operationalization during the COVID-19 pandemic and propose the strategic deployment of these technologies in collaboration with public health agencies. In addition, we address significant challenges and ethical considerations, such as AI biases, misinformation, privacy concerns, and the required regulatory oversight. We envision a future with leverages generalist CAI in messaging apps, proposing a multiagent approach to enhance the reliability and specificity of health communications. We hope this commentary initiates the necessary conversations and research toward building evaluation approaches, adaptive strategies, and robust legal and technical frameworks to fully realize the benefits of AI-enhanced communications in public health, aiming to ensure equitable and effective health outcomes across diverse populations.

摘要

将人工智能(AI)集成到健康通信系统中,为公共卫生管理引入了一种变革性方法,特别是在突发公共卫生事件期间,能够通过常见的数字渠道覆盖数十亿人。本文探讨了通用对话式人工智能(CAI)的效用和影响,这种先进的人工智能系统通过大量数据集进行训练,能够以类似人类的响应能力处理跨领域的各种对话任务。具体重点是通用CAI在消息服务中的应用,强调其增强公共卫生通信的潜力。我们突出了人工智能驱动的消息服务的发展历程和当前应用,包括它们提供个性化、可扩展且易于获取的健康干预措施的能力。具体而言,我们讨论了大语言模型和生成式人工智能在主流消息平台中的集成,这在公共卫生背景下可能优于传统信息检索系统。我们报告了对通用CAI在传递健康信息方面优势的批判性审视,以其在新冠疫情期间的实际应用为例,并提议与公共卫生机构合作对这些技术进行战略部署。此外我们还讨论了重大挑战和伦理考量,如人工智能偏差、错误信息、隐私问题以及所需的监管监督。我们设想了一个在消息应用程序中利用通用CAI的未来,提出一种多智能体方法来提高健康通信的可靠性和针对性。我们希望这篇评论能够引发必要的讨论和研究,以建立评估方法、适应性策略以及强大的法律和技术框架,从而充分实现人工智能增强通信在公共卫生领域的益处,旨在确保不同人群都能获得公平且有效的健康成果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb67/11791462/75c144fa0382/jmir_v27i1e69007_fig1.jpg

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