Alignment Games: A Framework for Conceptual Repair in Human-AI Collaboration
The meaning of a concept in use is shaped by the situation, task, goals, and prior knowledge. For example, a request to make a poster "visually appealing for a five-year-old" might evoke bright colors and cartoon imagery for one collaborator, but less text, bold shapes, and visual simplicity for another. We call such task-relevant differences conceptual misalignment. We introduce Alignment Games, a framework for making these differences visible and repairable during human-AI interaction. Drawing on theories of situated conceptualization, we characterize task-specific conceptual frames in terms of relevant attributes, values, relations, constraints, and priorities. We then define alignment...
| Authors | Hari Subramonyam, Maneesh Agrawala, Sean Follmer |
|---|---|
| Primary category | cs.HC |
| Published | 28 September 2026 |
| Last updated at source | 28 September 2026 |
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