信任发展与可解释性:个性化辅助系统纵向研究

Setareh Zafari, Jesse de Pagter, Guglielmo Papagni, Alischa Rosenstein, Michael Filzmoser, Sabine T. Koeszegi
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引用次数: 0

摘要

本文报告了一项纵向实验,该实验在七天时间内考察了辅助系统的故障和透明度对信任度的影响。为此,我们模拟了系统的个性化推荐功能,以支持参与者学习新课文和进行测验。采用 2 × 2 混合设计,系统故障(正确与错误)和透明度(有解释与无解释)作为被试间变量,而暴露时间则作为重复测量变量。我们采用定性和定量相结合的方法分析了 171 名参与者的数据。我们的结果表明,参与者认为系统做出错误的推荐是对信任的侵犯。此外,在定量和定性分析中还发现了一种趋势,即解释的可用性(即使在未访问的情况下)会增加对可信系统的感知。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trust Development and Explainability: A Longitudinal Study with a Personalized Assistive System
This article reports on a longitudinal experiment in which the influence of an assistive system’s malfunctioning and transparency on trust was examined over a period of seven days. To this end, we simulated the system’s personalized recommendation features to support participants with the task of learning new texts and taking quizzes. Using a 2 × 2 mixed design, the system’s malfunctioning (correct vs. faulty) and transparency (with vs. without explanation) were manipulated as between-subjects variables, whereas exposure time was used as a repeated-measure variable. A combined qualitative and quantitative methodological approach was used to analyze the data from 171 participants. Our results show that participants perceived the system making a faulty recommendation as a trust violation. Additionally, a trend emerged from both the quantitative and qualitative analyses regarding how the availability of explanations (even when not accessed) increased the perception of a trustworthy system.
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