Light Language Objects: Ambiguity and Otherness in Embodied AI

When AI talks like a person, people tend to treat it like one. Large language models match our language, tone, and emotional cues, which can make a hollow or inappropriate response feel personal. Most systems address this problem by making the model more humanlike. Light Language Objects explore another direction: what kinds of relationships become possible when AI is allowed to remain perceptibly other? We present Light Language Objects (LLOs), three embodied AI artifacts that listen to speech but respond only through color, brightness, rhythm, and movement. Because the model cannot answer in words, its responses remain ambiguous. The person interprets each light gesture and decides whether to save it. Over time, repeated expressions can form a small visual vocabulary whose meanings remain personal and open to change. Meaning is shaped by the model's proposals, the person's interpretations, the software's memory, and the physical limits of each lantern. LLOs examine whether this lower-resolution form of communication can support curiosity and empathic attention while keeping the AI clearly nonhuman.