Presented by:Sho Soboyejo
Are you tired of recommendation engines that feel generic? Today's recommendation systems still rely heavily on collaborative or content-based filtering. These models lack true insight into why people choose what they do. In this talk, we explore the next frontier: building recommendation systems that understand what users do and who they are. By integrating personality psychology (like the Big Five model) with the powerful capabilities of Large Language Models (LLMs), we can design systems that offer richer, more satisfying, and more explainable recommendations. Attendees will learn to move beyond clickstreams and ratings to leverage implicit signals, infer personality traits, and generate nuanced suggestions. This will be done while addressing challenges around cold starts, explainability, and user trust. Whether you're building for e-commerce, media, or travel, this session will expand your personalization toolkit and show how personality-driven design can unlock a new era of intelligent recommendations.