从集体人类意见到人工智能算法:建议来源如何影响对行为健康风险的判断
Mengying Liu1, Xiyu Guo1, Xiaoang Wan1
1Department of Psychological and Cognitive Sciences, Tsinghua University, Beijing, China.
Applied psychology. Health and well-being
|March 6, 2026
概括
人工智能 (AI) 过度估计了健康风险,但人们根据威胁水平不同地整合AI建议. 人类建议在低威胁情况中是首选的,而人工智能建议在高威胁情景中推动了更大的信念变化.
科学领域:
- 认知心理学 认知心理学
- 人与计算机的交互
- 卫生沟通健康沟通
背景情况:
- 咨询来源显著影响个人的风险感知和健康选择.
- 了解不同咨询来源 (人工智能与人类) 如何影响健康风险评估对于有效的决策至关重要.
研究的目的:
- 为了比较人工智能算法和人类同行群体之间的健康风险评估.
- 调查人工智能和人类建议如何影响对行为健康风险的判断.
- 探索威胁背景在人类-人工智能咨询整合中的作用.
主要方法:
- 实验1:参与者和人工智能 (GPT-4) 评价了60种健康行为的感知风险.
- 实验2:参与者在不同的威胁条件下接受人工智能或人类同行建议后,评估健康风险并修改判断.
主要成果:
- 人工智能系统地高估了健康风险,通过膨胀结果的严重程度,而不是概率.
- 参与者更喜欢在较低威胁条件下接受人类建议.
- 在更高的威胁条件下,接受不同意人工智能的建议的参与者比遵循人类建议的参与者显示出更大的信念更新.
结论:
- 威胁的背景显著调节个人如何整合人工智能与人类来源的建议.
- 研究结果为设计基于人工智能的健康决策支持系统提供了见解,这些系统可以有效利用人类-人工智能协作.
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