Browsing by Author "Tan, Libo"

This study explores how participatory algorithm design can empower gig workers by introducing a configurable Hungarian matching system on Open Deli, a localized food delivery platform. It implements a web-based prototype that allowed couriers to adjust and visualize preference-based matching configurations in real time. Through live study sessions with potential couriers, we found that preference-based matching (e.g., location, food type, compensation) enhanced perceptions of fairness and alignment, even among participants without algorithmic expertise. The study revealed trade-offs between flexibility and information overload, highlighting the need for intuitive preference elicitation. Overall, our findings suggest that transparent, collaborative systems can better reflect worker values and support more equitable gig work experiences.