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.
翻译：然而,当人类想教授人工智能时,现有的互动系统只能允许人类进行重复的标签,从而造成不令人满意的教学经验。 我的博士研究研究“交互式机器教学 ” ( IMT ) 。 交互式机器教学( IMT ) 是HCI研究的新兴领域,目的是提高人类在人工智能创建过程中的教学经验。 我的研究建立了利用和指导用户互动的IMT 系统,并表明这种深入的人类互动结合既有益于人工智能模型,也有利于用户经验。
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