Attune
Jenna Shon
We have become fluent in reading screens, but clumsy at reading each other. Tension goes unnoticed. Discomfort gets missed. Conversations tip to one side. These are not failures of character but small, everyday failures of awareness. Awareness is something technology can quietly support, without taking over the human instinct behind it.
This project proposes Attune, an AI-driven product that translates invisible social signals into motion-based feedback. Four features address key moments of social navigation: reading room atmosphere, tracking conversational balance, detecting discomfort, and revealing one's own emotional state before communication. Each feature draws from existing sensors—microphones capture vocal patterns and acoustic data, smartwatches measure physiological signals like heart rate variability and skin temperature, and devices log behavioral patterns in typing and app usage.
AI analyzes these inputs in real time, identifying patterns that reveal emotional states. The visual language uses motion grounded in heuristic approaches, like water drops merging, sand piling up, knots forming, and breath expanding and contracting. Each motion is designed to feel visceral and immediate, bypassing cognition to speak directly to intuition.
The design prioritizes awareness over instruction. The product does not tell users how to act; it provides information and then steps back. The goal is a functional tool for social navigation that supports human judgment rather than replacing it.