人们根据驱动其行为的算法来评估代理
1Department of Psychology, Harvard University, Cambridge, MA, USA.
Open mind : discoveries in cognitive science
|September 17, 2025
概括
评估代理的人会考虑底层算法,而不仅仅是性能. 这项研究揭示了人类是直观的认知主义者,重视知识的价值.
科学领域:
- 认知科学 认知科学
- 人工智能的人工智能
- 人与计算机的交互
背景情况:
- 人类通过考虑可观测的指标或潜在的计算过程来直观地评估代理的性能.
- 区分直观行为主义 (关注外部表现) 和直观认知主义 (关注内部算法) 对于理解人类判断至关重要.
研究的目的:
- 调查人们在评估代理时是否优先考虑外部绩效指标或内部算法过程.
- 提出和测试一个有三个维度的框架:行动效率,表现效率和概括,以区分直观行为主义和认知主义.
主要方法:
- 对598名参与者进行了一项实验,评估了一对迷宫解决剂及其基础程序.
- 代理人得到了一个单一的迷宫解决示例,在三个拟议的维度中对变化.
- 参与者选择了"更好的"计划,允许分析他们的评价标准.
主要成果:
- 拟议的框架成功地预测了参与者在实验任务中的方案选择.
- 结果表明,参与者倾向于基于其潜在算法属性的程序.
- 证据支持这样的假设,即人类的评估超越了单纯的表现,包括了算法考虑.
结论:
- 人类表现为直观的认知学家,考虑代理人的内部算法,而不是仅仅专注于外部性能.
- 这些发现对设计与人类直观判断一致的AI系统以及理解人类-AI互动有重要意义.
- 未来的研究可以在更复杂的代理行为和任务中探索这些维度的细微差别.
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