arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2008.09100cs.HCcs.AIcs.LG
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领域专家在用户信任中的作用以及首次使用智能系统的影响

The Role of Domain Expertise in User Trust and the Impact of First Impressions with Intelligent Systems

University of Florida(佛罗里达大学);Texas A&M University(得克萨斯农工大学)

Mahsan Nourani, Joanie T. King, Eric D. Ragan

摘要:

特定领域的智能系统旨在帮助系统用户进行决策。许多系统的目标是同时支持不同级别的领域专业知识的不同用户,但先验领域知识会影响用户的信任和信心,在检测系统错误。虽然它也是已知的,用户的信任可以通过第一印象与智能系统的影响,我们的研究探讨了排序偏差和领域的专业知识之间的关系时,遇到错误的智能系统。在本文中,我们提出了一个控制用户的研究,探讨领域知识的作用,建立信任和易感性的影响,第一印象对用户的信任。参与者审查了一个可解释的图像分类器,具有恒定的准确性和两个不同的观察系统错误的顺序(观察错误的开始使用与结束)。我们的研究结果表明,早期遇到错误可能会给领域专家造成负面的第一印象,在互动过程中对他们的信任产生负面影响。然而,尽早遇到正确的输出有助于更有知识的用户根据他们对系统性能的观察动态地调整他们的信任。相比之下,新手用户由于缺乏适当的知识来检测错误而遭受过度依赖。

英文摘要:

Domain-specific intelligent systems are meant to help system users in their decision-making process. Many systems aim to simultaneously support different users with varying levels of domain expertise, but prior domain knowledge can affect user trust and confidence in detecting system errors. While it is also known that user trust can be influenced by first impressions with intelligent systems, our research explores the relationship between ordering bias and domain expertise when encountering errors in intelligent systems. In this paper, we present a controlled user study to explore the role of domain knowledge in establishing trust and susceptibility to the influence of first impressions on user trust. Participants reviewed an explainable image classifier with a constant accuracy and two different orders of observing system errors (observing errors in the beginning of usage vs. in the end). Our findings indicate that encountering errors early-on can cause negative first impressions for domain experts, negatively impacting their trust over the course of interactions. However, encountering correct outputs early helps more knowledgable users to dynamically adjust their trust based on their observations of system performance. In contrast, novice users suffer from over-reliance due to their lack of proper knowledge to detect errors.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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