AI助手实时辅助面试，减轻访谈者认知负担。
Interview AI-ssistant: Designing for Real-Time Human-AI Collaboration in Interview Preparation and Execution
- 设计实时人机协作系统，支持面试准备与执行。
- 通过四阶段研究验证系统有效性，提升访谈质量。
- 适合研究者与需要深度访谈的团队使用。
大型语言模型（LLMs）为提升定性研究方法中的访谈质量提供了前所未有的机遇。尽管访谈能获取深层、情境化的见解，但访谈者常面临实时信息处理、问题调整和关系维护等认知挑战。本博士研究提出“Interview AI-ssistant”系统，支持访谈前准备与执行阶段的人机实时协作。通过四个相互关联的研究：访谈者需求的形成性研究、基于AI的访谈准备原型开发、访谈中实时辅助的实验评估，以及在真实研究场景中的实地部署，本研究探索了复杂社会任务中有效人机协作的设计。研究成果不仅推动智能访谈支持系统的实际应用，也深化了智能用户界面（IUI）领域对复杂社交任务中人机协同界面的理解，并提出了面向人工智能增强型定性研究工具的设计指南。
原文摘要 · Abstract (English)
Recent advances in large language models (LLMs) offer unprecedented opportunities to enhance human-AI collaboration in qualitative research methods, including interviews. While interviews are highly valued for gathering deep, contextualized insights, interviewers often face significant cognitive challenges, such as real-time information processing, question adaptation, and rapport maintenance. My doctoral research introduces Interview AI-ssistant, a system designed for real-time interviewer-AI collaboration during both the preparation and execution phases. Through four interconnected studies, this research investigates the design of effective human-AI collaboration in interviewing contexts, beginning with a formative study of interviewers' needs, followed by a prototype development study focused on AI-assisted interview preparation, an experimental evaluation of real-time AI assistance during interviews, and a field study deploying the system in a real-world research setting. Beyond informing practical implementations of intelligent interview support systems, this work contributes to the Intelligent User Interfaces (IUI) community by advancing the understanding of human-AI collaborative interfaces in complex social tasks and establishing design guidelines for AI-enhanced qualitative research tools.
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