"Oops! ChatGPT is Temporarily Unavailable!": A Diary Study on Knowledge Workers' Experiences of LLM Withdrawal
arXiv cs.AI / 3/30/2026
💬 OpinionIdeas & Deep AnalysisModels & Research
Key Points
- A four-day diary study with frequent LLM users examined how knowledge workers experienced a temporary LLM withdrawal and how quickly workflows were disrupted.
- The researchers found that withdrawal exposed gaps in task execution, suggesting participants had become dependent on LLM support for parts of their work.
- Participants’ self-directed responses included reclaiming professional values, indicating coping and recovery behaviors that go beyond simply “restarting” the tool.
- The study characterizes LLMs as infrastructural—so embedded that everyday practices make their use effectively normative even when the system is absent.
- The authors propose “value-driven appropriation” as an approach for supporting professional values in environments where LLMs are pervasive and hard to ignore.
Related Articles
Freedom and Constraints of Autonomous Agents — Self-Modification, Trust Boundaries, and Emergent Gameplay
Dev.to
Von Hammerstein’s Ghost: What a Prussian General’s Officer Typology Can Teach Us About AI Misalignment
Reddit r/artificial
Stop Tweaking Prompts: Build a Feedback Loop Instead
Dev.to
Privacy-Preserving Active Learning for autonomous urban air mobility routing under real-time policy constraints
Dev.to
The Prompt Tax: Why Every AI Feature Costs More Than You Think
Dev.to