Co-Constructing Alignment: A Participatory Approach to Situate AI Values

TL;DR

This paper proposes a participatory, interaction-focused approach to AI alignment, emphasizing user engagement and situated practices over model-centric methods.

Contribution

It introduces a participatory workshop method combining misalignment diaries and design activities to understand and co-construct alignment in AI systems.

Findings

Misalignments are experienced as unexpected responses or breakdowns, not just ethical issues.

Users adopt diverse roles, including adjusting, interpreting, or deliberately ignoring model responses.

Alignment is seen as an ongoing, shared practice rather than a fixed property.

Abstract

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.