As AI systems become embedded in everyday practice, value misalignment has emerged as a pressing concern. Yet, dominant alignment approaches remain model centric, treating users as passive recipients of prespecified values rather than as epistemic agents who encounter and respond to misalignment during interactions. Drawing on situated perspectives, we frame alignment as an interactional practice co-constructed during human AI interaction. We investigate how users understand and wish to contribute to this process through a participatory workshop that combines misalignment diaries with generative design activities. We surface how misalignments materialise in practice and how users envision acting on them, grounded in the context of researchers using Large Language Models as research assistants. Our findings show that misalignments are experienced less as abstract ethical violations than as unexpected responses, and task or social breakdowns. Participants articulated roles ranging from adjusting and interpreting model behaviour to deliberate non-engagement as an alignment strategy. We conclude with implications for designing systems that support alignment as an ongoing, situated, and shared practice.

翻译：随着人工智能系统嵌入日常实践，价值对齐已成为一个紧迫问题。然而，主流对齐方法仍以模型为中心，将用户视为预设价值观的被动接受者，而非在交互过程中遭遇并回应错位的认知主体。基于情境化视角，我们将对齐视为人机交互过程中共同构建的互动实践。通过结合错位日记与生成式设计活动的参与式研讨会，我们探究用户如何理解并希望参与这一过程。本研究以使用大型语言模型作为研究助手的研究人员为背景，揭示了错位如何在实践中具体体现，以及用户如何设想应对这些错位。研究发现，错位更常被体验为意外回应、任务或社交中断，而非抽象的伦理违规。参与者阐述了从调整和解释模型行为到将刻意不参与作为对齐策略等不同角色定位。最后，我们探讨了如何设计支持持续、情境化且共享的对齐实践的系统。