Assessing Human-AI Interaction Early through Factorial Surveys: A Study on the Guidelines for Human-AI Interaction
Assessing Human-AI Interaction Early through Factorial Surveys: A Study on the Guidelines for Human-AI Interaction
复制标题
通过析因调查尽早评估人机交互：人机交互指南研究
DOI：
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Saleema Amershi
中科院分区：
文献类型：
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作者：
Tianyi Li;Mihaela Vorvoreanu;Derek DeBellis;Saleema Amershi
这项工作有助于在特定AI产品的背景下评估人类与AI交互的研究协议。该研究协议使UX和HCI研究人员能够在投资工程之前评估不同的人机交互解决方案并验证设计决策。我们详细介绍了研究协议，并通过使用它来研究现有的一套人类-AI交互指南来展示其用途。我们使用2 × 2混合设计的析因调查来比较在最佳与次优AI性能条件下应用与违反指南时的用户感知。结果为每个指南的用户体验影响提供了定性和定量的见解。这些见解可以支持面向用户的人工智能系统的创建者对指导方针进行细致入微的优先级排序和应用。
This work contributes a research protocol for evaluating human-AI interaction in the context of specific AI products. The research protocol enables UX and HCI researchers to assess different human-AI interaction solutions and validate design decisions before investing in engineering. We present a detailed account of the research protocol and demonstrate its use by employing it to study an existing set of human-AI interaction guidelines. We used factorial surveys with a 2 × 2 mixed design to compare user perceptions when a guideline is applied versus violated, under conditions of optimal versus sub-optimal AI performance. The results provided both qualitative and quantitative insights into the UX impact of each guideline. These insights can support creators of user-facing AI systems in their nuanced prioritization and application of the guidelines.
定制场景：一种低成本在线方法，利用参与者特定的上下文信息来引发对家庭技术的看法
影响因子：
1.3
作者：
Brown M
通讯作者：
Brown M
DOI：
10.1145/3313831.3376255
发表时间：
2020-04
期刊：
Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
影响因子：
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作者：
Madiha Tabassum;Jessica Kropczynski;P. Wisniewski;H. Lipford
通讯作者：
Madiha Tabassum;Jessica Kropczynski;P. Wisniewski;H. Lipford