Pillpack People

I led visual and interaction design for Pillpack People, an augmented intelligence project developed at CoLab with Reid Williams and Parker Woodworth, creating live code sketches of interactions and visualizations that Parker implemented in the final prototype. Our approach emerged from discovering patterns in anonymized customer data that resembled user personas, prompting us to develop a system that could visualize these trait sets to foster empathy while preserving customer privacy. The interface allows users to adjust trait sliders on the left side, which dynamically generates a representative face with corresponding emotional expressions—ranging from happy and laughing to angry or shouting—along with a procedurally generated name, backstory, and location based on broader user groups. This provides customer service representatives with instant visual feedback about the potential emotional state of the person they're assisting. I custom-illustrated over 100 SVG components—including face shapes, eyes, brows, noses, mouths, and facial hair—on a precise vertical and horizontal grid system, each weighted differently in a randomization algorithm that generates a unique face whenever slider values change. Behind each generated face appears a unique watercolor splash that shifts in color and shape with each new generation, using warmer tones to indicate anger and cooler tones for contentment, with the animation achieved through masked PNG animations and SVG filters for color interpolation—allowing the system to communicate customer mood quickly with minimal text.