研究知识工作者短暂断开大模型后的应对，揭示其依赖与专业价值重塑。
"Oops! ChatGPT is Temporarily Unavailable!": A Diary Study on Knowledge Workers' Experiences of LLM Withdrawal
- 通过四天日记研究，观察10位高频使用者断开大模型后的反应。
- 发现断连导致任务执行中断，暴露出对大模型的深度依赖。
- 适合关注AI依赖、职场伦理与人机协同的研究者和从业者。
大语言模型已深度嵌入知识工作，引发对依赖性及人类能力弱化的担忧。为探究大模型在工作中的普遍性影响，我们对10名高频使用者开展为期四天的日记研究，观察其在大模型临时不可用时的应对方式。研究发现，断连导致任务执行出现空白，暴露了对大模型的严重依赖；同时，自主工作促使参与者重新审视职业价值；日常实践也揭示出大模型使用已成为无法回避的规范。将大模型视为当代知识工作的基础设施，本研究提供了关于其隐性作用的实证洞察，并提出以价值观为导向的使用策略，以在大模型广泛渗透的工作环境中维护专业价值。
原文摘要 · Abstract (English)
LLMs have become deeply embedded in knowledge work, raising concerns about growing dependency and the potential undermining of human skills. To investigate the pervasiveness of LLMs in work practices, we conducted a four-day diary study with frequent LLM users (N=10), observing how knowledge workers responded to a temporary withdrawal of LLMs. Our findings show how LLM withdrawal disrupted participants' workflows by identifying gaps in task execution, how self-directed work led participants to reclaim professional values, and how everyday practices revealed the extent to which LLM use had become inescapably normative. Conceptualizing LLMs as infrastructural to contemporary knowledge work, this research contributes empirical insights into the often invisible role of LLMs and proposes value-driven appropriation as an approach to supporting professional values in the current LLM-pervasive work environment.
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