论文标题
在互动机教学中利用和指导用户互动
Exploiting and Guiding User Interaction in Interactive Machine Teaching
论文作者
论文摘要
人类具有在教学过程中进行多种互动的能力才有才华。但是，当人类想教AI时，现有的交互式系统只允许人类执行重复的标签，从而导致教学经验不令人满意。我的博士学位研究研究互动机器教学（IMT），这是一个新兴的HCI研究领域，旨在增强人类在AI创建过程中的教学经验。我的研究构建了IMT系统，可利用和指导用户互动，并表明人类互动的这种深入整合可以使AI模型和用户体验受益。
Humans are talented with the ability to perform diverse interactions in the teaching process. However, when humans want to teach AI, existing interactive systems only allow humans to perform repetitive labeling, causing an unsatisfactory teaching experience. My Ph.D. research studies Interactive Machine Teaching (IMT), an emerging field of HCI research that aims to enhance humans' teaching experience in the AI creation process. My research builds IMT systems that exploit and guide user interaction and shows that such in-depth integration of human interaction can benefit both AI models and user experience.
