Machine Eye

Large language models (LLMs) are increasingly embodied as assistants, companions, and collaborators, framing AI through familiar human roles that prescribe how agency should be understood and exercised. \textit{Machine Eye} is an AI artwork that deliberately resists these metaphors, presenting as a deliberately ambiguous artefact whose role is left unresolved. The object observes its surroundings through computer vision and ambient audio, generating an ongoing stream of internal "thoughts" using an LLM. These reflections are revealed only by looking through the object itself, positioning viewers as witnesses to its perspective. The work explores how we make sense of these systems when use is not prescribed in description or embodiment, where agency emerges through interaction. Without explicit instructions for how it should be understood, viewers negotiate their own relationship with the artefact, attributing intention, personality, curiosity, care, or indifference as they encounter its behaviour. \textit{Machine Eye} therefore shifts attention from AI as an instrument of human agency towards AI as a participant in a shared relational space, where agency is distributed, interpreted, and continually renegotiated between the system, the audience, and its environment.