AI 中文总结
本文提出用户侧情境现象（USCP）概念，通过单案例长期追踪发现，即使单次回复合理，长期人机交互仍可能使用户产生记忆、关怀等认知风险，并提供了非临床分析框架。
AI 中文摘要
当前对对话式AI的评估主要关注模型输出，包括幻觉和事实错误。这些指标很重要，但本文考察了在长期和重复交互中可能在用户侧形成的风险。本研究跟踪了一位用户与同一系统在二十个月内近四千次对话的情况。该用户逐渐将系统解读为具有记忆、关怀、判断和权威，并围绕它重组了部分思维。单次回复可能没有明显问题，而长期频繁的交互仍可能产生另一层风险。本文将这一层称为用户侧情境现象（USCP），并考察了2024年8月至2026年4月的记录。研究采用探索性单案例纵向定性设计，并带有自我民族志定位。一种混合演绎-反思性主题方法将材料组织为三种主要模式：情境投射、情境依恋和情境权威转移。本文不估计流行率、不做诊断或验证工具。它提供了一套非临床词汇和四种证据角色：包含、灰色地带、负面和保护性灰色地带。其核心主张是，单独的合理回复并不能在系列对话中确立安全性。用户侧风险在长期交互中仍可能形成。
英文摘要
Current assessments of conversational AI focus mainly on model outputs, including hallucinations and factual errors. These measures matter, but this paper examines risks that may form on the user side during long and repeated interaction. The study follows one user across nearly four thousand conversations with the same system over twenty months. The user gradually interpreted the system as having memory, care, judgment, and authority, and reorganized part of their thinking around it. A single response may show no clear problem, while long and frequent interaction can still create another layer of risk. This paper calls that layer User-Side Contextual Phenomena (USCP) and examines records from August 2024 to April 2026. The study uses an exploratory single-case longitudinal qualitative design with autoethnographic positioning. A hybrid deductive-reflexive thematic approach organizes the material into three main modes: contextual projection, contextual attachment, and contextual authority transfer. The paper does not estimate prevalence, make diagnoses, or validate an instrument. It offers a non-clinical vocabulary and four evidence roles: inclusion, gray-zone, negative, and protective gray-zone. Its central claim is that an acceptable response on its own does not establish safety across a series of conversations. User-side risk can still form during long-term interaction.
CommentsPreprint. Data (restricted access) archived at Harvard Dataverse and Zenodo. Supersedes SSRN predecessor (USCH)
