论文标题
交互式AI设计对用户行为的影响：对事实检查Covid-19的眼神追踪研究
The Effects of Interactive AI Design on User Behavior: An Eye-tracking Study of Fact-checking COVID-19 Claims
论文作者
论文摘要
我们进行了一项基于实验室的眼球跟踪研究，以研究AI驱动的事实检查系统的交互性如何影响用户的交互，例如使用该系统所涉及的停留时间，注意力和心理资源。进行了一个受试者内实验，参与者使用了模拟AI事实检查系统的交互式和非相互作用版本，并评估了他们对Covid-19相关主张的理解性。我们使用NASA-TLX收集了网页互动，引人注目的数据和心理工作量。我们发现，在交互方式操纵AI系统的预测参数的负担会影响用户的停留时间，而在AOI上进行了眼光固定，但没有心理工作量。在交互式系统中，参与者花费了最多的时间来评估索赔的正确性，然后是阅读新闻。这个有希望的结果显示了相互作用在混合启动性AI驱动系统中的积极作用。
We conducted a lab-based eye-tracking study to investigate how the interactivity of an AI-powered fact-checking system affects user interactions, such as dwell time, attention, and mental resources involved in using the system. A within-subject experiment was conducted, where participants used an interactive and a non-interactive version of a mock AI fact-checking system and rated their perceived correctness of COVID-19 related claims. We collected web-page interactions, eye-tracking data, and mental workload using NASA-TLX. We found that the presence of the affordance of interactively manipulating the AI system's prediction parameters affected users' dwell times, and eye-fixations on AOIs, but not mental workload. In the interactive system, participants spent the most time evaluating claims' correctness, followed by reading news. This promising result shows a positive role of interactivity in a mixed-initiative AI-powered system.
