模拟接受临床决策支持的认知过程
Leendert van Maanen1, Dominik Bachmann1,2, Talha Özüdoğru1
1Experimental Psychology & Helmholtz Institute, Utrecht University, Utrecht, Netherlands.
概括
由于对算法的厌恶,人们犹是否相信算法. 这项研究表明,算法厌恶涉及在决策中提高谨慎性,而不是降低感知可靠性,影响人类-人工智能协作.
科学领域:
- 认知心理学 认知心理学
- 人工智能伦理学 人工智能伦理学
- 临床决策支持 临床决策支持
背景情况:
- 算法厌恶是一种不信任算法建议的倾向,即使算法建议优于人类输入.
- 了解算法厌恶的认知基础对于在医学等关键领域有效的人类-人工智能合作至关重要.
研究的目的:
- 在临床决策背景下调查驱动算法厌恶的认知机制.
- 区分增加的谨慎性和减少的可靠性作为算法厌恶的原因.
主要方法:
- 两项实验涉及参与者评估X射线骨折骨折的建议,无论是算法或人类.
- 利用证据积累建模来分析决策门和响应时间.
- 当人类建议归因于非专业人士与专家放射科医生时,我们比较了决策策略.
主要成果:
- 参与者表现出更长的响应时间,并为算法建议设置了更高的决策值,表明了更大的审议和谨慎.
- 这种高度谨慎仍然存在,无论人类的建议来自于普通参与者还是专家放射科医生.
- 在算法和人类咨询来源之间的证据积累率或先前偏好方面没有发现显著差异.
结论:
- 算法厌恶的特点是决策谨慎性的战略性增加,而不是对算法可靠性的感知减弱.
- 正式的认知模型对于理解对自动化系统的信任和优化人与算法的协作是有价值的.
- 识别响应谨慎作为一个核心机制,推进了对算法厌恶的理论理解.
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