开源平台AInterviewer用多智能体实现安全可控的AI访谈，兼顾灵活性与规范性。
AInterviewer: A Platform for Designing and Conducting AI-led Qualitative Interviews
- 采用多智能体流水线，结合问卷软件的控制力与LLM的灵活性
- 支持本地部署模型，保障数据安全与结果可复现
- 提供全流程网页界面，覆盖设计、测试到数据监控
目前基于大语言模型（LLMs）的自动化定性访谈系统大多依赖专有模型，影响可复现性与数据安全，且全程由LLM处理问题，导致问题表述不统一、顺序不可控。为此，我们提出AInterviewer平台，一个开源的多智能体架构系统，将调查软件的受控问题发布能力与LLM的灵活应答优势结合。该平台跨学科设计，遵循社会科学定性访谈的最佳实践，支持本地化模型运行，确保安全性、透明度与可复现性。平台提供基于网页的图形界面，覆盖访谈指南设计、预测试、分发及数据收集监控等全阶段流程。
原文摘要 · Abstract (English)
There are now multiple proposals for systems based on Large Language Models (LLMs) to conduct automated qualitative interviews, but most of the current solutions rely on proprietary LLMs, which compromises reproducibility and data security. They also rely on LLMs for all interview tasks, which limits standardisation of question wording as well as control over question order. To address these issues, we introduce the AInterviewer platform, an opensource solution based on a multi-agent pipeline that combines controlled question administration of survey software with the flexibility of LLMs. AInterviewer is an interdisciplinary effort designed to implement best practices of qualitative interviewing in social science, and it can run with locally hosted models to ensure security, transparency, and reproducibility. Our platform provides a web-based GUI supporting each phase of data collection: from interview guide design and pilot testing to interview distribution and data collection monitoring.
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