AI 中文总结
研究聚焦于主观体验研究中深度与规模的权衡问题，核心方法是将描述性经验抽样法转化为人工智能访谈者的推理架构，主要贡献是开发出首个基于既定方法研究内心体验的人工智能访谈者及相关平台。
AI 中文摘要
主观体验是心理学的核心，但研究方法在深度和规模之间存在权衡。经典的经验抽样法（如生态瞬时评估）能捕捉即时体验，但限制了参与者的回答格式。描述性经验抽样法虽能深入研究特定时刻，但依赖稀缺的训练有素的访谈者，样本量小。大语言模型系统可扩展定性访谈，但缺乏基于理解内心体验的方法。本文提出一种人工智能访谈者，将描述性经验抽样法转化为明确、可检查的推理架构，从描述性经验抽样法的完整转录本中推导而来，并与该方法的创始人进行了完善。它运行在Introscope应用程序中，该应用程序发出提示音并进行访谈，还提供研究平台。在等待验证研究期间，将向研究人员和公众免费提供，用于众包抽样和个人内心体验探索。
英文摘要
Subjective experience is central to psychological science, yet methods for studying it force a choice between depth and scale. Classical Experience sampling, as in ecological momentary assessments (EMA), captures experience as it occurs, but it confines participants to predetermined response formats that prescribe how experience is measured. Descriptive Experience Sampling (DES) instead investigates specific moments in depth through expert expositional interviews, but its reliance on scarce trained interviewers keeps samples small. Large language model (LLM) systems can scale qualitative interviewing. Some models operationalize established interviewing methods such as motivational interviewing, yet none is grounded in a method for apprehending inner experience. Here we present an AI interviewer that aspires to operationalize DES into an explicit, inspectable reasoning architecture. At each turn it appraises the participant's message across eleven quality dimensions, maintains a conservative account of what has been established, selects a stage-appropriate intervention, and composes a single non-leading query, always holding that temporal grounding precedes experiential content. It was derived from the full corpus of DES transcripts and refined with the method's originator Russell T. Hurlburt. To our knowledge it is the first AI interviewer grounded in an established method for studying inner experience. The interviewer runs inside Introscope, an application that delivers the beeps and conducts the interviews and a study platform that lets researchers run studies via shareable links and review the sampled experience. It is demonstrated in an accompanying video https://introscope.mpib-berlin.mpg.de/video. Pending validation studies, we will make it freely available to researchers and the public, for crowdsourced sampling and individual exploration of inner experience.
