驱动因素和社会一致性对人类-人工智能团队决策的影响
Huixin Zhong1,2, Jack McKinlay2, Jinha Yoon2
1School of Smart Governance, Renmin University of China, Suzhou, 215123, China.
Scientific reports
|March 14, 2026
概括
人工智能 (AI) 代理人不像人类同行那样产生规范影响,影响团队决策. 虽然人工智能和人类提供了类似的信息影响,但由于社会认可需求,人们更喜欢人类,这种偏见随着复杂的准确性线索而减少.
科学领域:
- 决策科学 决策科学
- 人与计算机的交互
- 人工智能的人工智能
背景情况:
- 社会一致性通过信息和规范压力影响人类团队的决策.
- 这些符合性驱动器的可转移到混合人-人工智能团队仍然是一个开放的研究问题.
- 了解AI在社会动态中的作用对于有效的人类-AI合作至关重要.
研究的目的:
- 调查人工智能代理人是否引起与人类同行可比的社会一致性效应.
- 确定信息和规范影响是否转移到AI队友.
- 检查人类如何在决策任务中权衡人工智能与人类顾问的建议.
主要方法:
- 两项研究采用了医疗信息级联模式,与混合的人类-人工智能团队合作.
- 参与者从人工智能或人类顾问那里获得私人证据和公共建议.
- 研究1比较建议权重,当信息准确性是相同的;研究2的准确性各不相同.
主要成果:
- 人工智能和人类对信息的影响是相似的;与贝叶斯基准相比,参与者对两者建议的权重不足.
- 规范性影响有所不同:在研究1中,参与者更喜欢人类建议,而不是同样可靠的AI建议.
- 这种规范性偏见在研究2中消失了,当整合变量准确性和多数共识时,所有建议的权重不足.
结论:
- 对人工智能与人类建议的依赖差异源于缺乏规范性影响,而不是缺乏信息信任.
- 人工智能缺乏人类同行的规范性吸引力,影响混合团队中的合规动态.
- 异质的准确性线索可以增加认知负载,从而导致人类和人工智能建议的最佳集成.
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