人工智能驱动的治理:通过以预防风险为中心的综合风险管理模式来应对新出现的风险,用于公共卫生危机管理
Ching-Hung Lee1, Zhichao Wang1, Dianni Wang1
1School of Public Policy and Administration, Xi'an Jiaotong University1, Xi'an, China.
Health research policy and systems
|September 27, 2025
概括
人工智能 (AI) 在流行病预防方面受到公众的接受至关重要. 以风险预防为中心和启用人工智能的抗流行技术接受模型 (RPAA-TAM) 确定了影响公共卫生危机人工智能采用的关键因素.
科学领域:
- 公共卫生 公共卫生
- 人工智能的人工智能
- 技术采用 技术采用
背景情况:
- 随着COVID-19的爆发,人们越来越需要人工智能支持的疫情预防技术.
- 了解公众对这些数字工具的采用对于有效的危机管理至关重要.
研究的目的:
- 开发一个全面的模型,以了解公众对人工智能的接受,以预防流行病.
- 确定影响采用人工智能驱动的抗流行病工具的关键因素.
主要方法:
- 构建了以风险预防为中心,并支持人工智能的抗流行病技术接受模型 (RPAA-TAM).
- 综合技术接受模型 (TAM),社会影响理论和风险感知理论.
- 分析了技术发展和影响公众接受人工智能的因素.
主要成果:
- 确定了影响公众接受的七个关键因素:外部变量,公众信任,感知好处,感知风险,对使用的态度,使用行为意图和系统使用.
- 从基于RPAA-TAM的文献综述中获得了七个新的建议.
- 提供了关于整合人工智能用于管理公共卫生危机的见解.
结论:
- "RPAA-TAM"为了解公众对人工智能在疫情预防中的接受提供了一个框架.
- 该研究提出了指导人工智能的伦理和社会可接受整合的新建议.
- RPAA-TAM为公共卫生危机的创新治理策略做出了贡献.
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