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：随着人工智能系统日益融入日常实践，价值观错位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应对错位的认知主体。借鉴情境化视角，我们将对齐框架化为一种在人类-人工智能交互过程中协同构建的互动实践。通过结合错位日记与生成式设计活动的参与式工作坊，我们探究了用户如何理解并期望参与这一过程。基于研究人员使用大型语言模型作为研究助理的语境，我们揭示了错位如何在实践中具体呈现，以及用户如何设想对其采取行动。研究发现表明，错位体验更多表现为意外响应、任务或社交中断，而非抽象的伦理违背。参与者阐述了从调整和解释模型行为到策略性不介入等多种角色，并将其作为对齐策略。最后，我们探讨了设计支持对齐作为持续性、情境化及共享实践的系统所蕴含的意义。