有意义的沟通,但不是肤浅的人类形象化促进人机信任校准:人机信任期望模型 (HATEM)
Owen B J Carter1, Shayne Loft1, Troy A W Visser1
1The University of Western Australia, Australia.
Human factors
|December 2, 2023
概括
自动化中的人类形态只会提高用户的信任,当它传达有用的信息,而不仅仅是通过外观. 有意义的沟通是衡量人类对自动化系统的信任的关键.
科学领域:
- 人与计算机的交互
- 自动化和机器人技术
- 认知心理学 认知心理学
背景情况:
- 人类形象主义被假设是为了增强人类-自动化信任,但经验证据是不确定的.
- 人类-自动化信任预期模型 (HATEM) 表明,人形主义的好处取决于促进关键信息的自然沟通.
- 有效的沟通对于预测自动化故障和校准信任至关重要.
研究的目的:
- 调查人类形象主义是否增强了人类对自动化的信任.
- 为了确定人形外观或有意义的沟通是否影响信任校准和信心.
- 为了测试HATEM的预测,语境信息对于人类形象主义的有效性至关重要.
主要方法:
- 使用潜艇潜镜模拟任务,98名本科生与船舶自动化建模 (SAM) 系统进行互动 (50%可靠性).
- 一个2x3的主体之间的设计操纵了SAM的外观 (人形化身对照相机眼) 和语音 (单调,无意义,有意义).
- 有意义的曲传达了关于自动化建议的确定性/不确定性的上下文相关信息.
主要成果:
- 虽然人类形态的外表被感知到,但它没有显著影响主观信任,信任校准或信心.
- 被评为更具人形 (无意义,有意义) 的语音曲线显示,对单调而言没有信任益处.
- 最重要的是,有意义的语音曲折显著改善了信任校准和信心,而不是单调和无意义的曲折.
结论:
- 人类形象主义对人类-自动化信任的影响是最小的,除非它有效地传达上下文相关信息.
- 有意义的沟通,而不仅仅是人形设计,对于准确的信任校准和用户信心至关重要.
- 设计师必须优先考虑通过人形特征传达的信息内容,以有效地管理用户的信任.
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