Weizi Liu

Rethinking User Empowerment in AI Recommender System: Innovating Transparent and Controllable Interfaces

AI-driven recommender systems are often perceived as personalization black boxes, limiting users’ ability to understand how their data shapes content (information asymmetry) or to influence system behavior meaningfully (power asymmetry). This study explores how design can strengthen user agency by integrating transpar…