Chatbot at the Table: Rethinking Group Recommendations with GenAI
For over two decades, group recommender systems (GRS) have been a curiosity in academic circles, promising collective decisions through algorithmic aggregation. Yet despite dozens of papers and prototype systems, they’ve failed to find traction in the real world. Netflix doesn’t use them. Spotify doesn’t bother. Most of us still hash out group decisions in a group chat—awkwardly, inefficiently, and without algorithmic help. The authors of a recent perspective paper argue it’s time for a fundamental reorientation: stop building tools that compute what the group should want, and start designing agents that help the group decide. With the rise of generative AI and agentic LLMs, the timing couldn’t be better. ...