人与人工智能的协作:性能和偏好之间的权衡.
Lukas W Mayer1, Sheer Karny2, Jackie Ayoub3
1Department of Cognitive Sciences, University of California, Irvine, Irvine, CA, USA. lwmayer@uci.edu.
Cognitive research: principles and implications
|February 27, 2026
概括
人们更喜欢协作的人工智能 (AI) 代理商,他们考虑人类的行为,而不是那些只专注于表现的人. 以人为中心的人工智能设计增强了可爱性,而不牺牲有效性,促进有意义的人类贡献.
科学领域:
- 人与计算机的交互
- 人工智能的人工智能
- 认知科学 认知科学
背景情况:
- 将人类投入整合到协作人工智能 (AI) 系统中,带来了重大设计挑战.
- 了解人类偏好对于开发有效的人类-人工智能合作至关重要.
研究的目的:
- 系统地调查人类对不同适应策略的协作AI代理人的偏好.
- 确定影响人类选择的人类-AI合作的因素.
主要方法:
- 开发了一个任务来评估五个具有不同适应策略的协作AI代理.
- 参与者与代理人互动,评估其特征,并选择首选的代理人.
- 采用贝叶斯模型来分析代理策略,团队表现,感知AI特征和人类偏好.
主要成果:
- 考虑人类行动的协作AI代理者比性能最大化的代理者更受青.
- 以人为中心的AI设计改善了AI合作者的可爱性,而不会影响团队的表现.
- 不平等的厌恶被确定为一个关键的驱动力,人类更喜欢那些能够有意义地贡献的代理.
结论:
- 以人为中心的设计原则对于开发可爱和有效的AI合作者至关重要.
- 与客观绩效指标平衡主观偏好对于成功的人类-人工智能合作至关重要.
- 解决人类对有意义贡献的渴望可以提高人工智能系统的接受度和实用性.
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