Getting virtually personal: making responsible and empathetic "her" for everyone

Abstract

Have you watched the movie Her? Have you ever wondered or wished to have your own AI companion just like Samantha, who could understand you better than you know about yourself, and could tell you what you really are, whom your best partner may be, and which career path would be best for you? In this talk, I will present a computational framework for building responsible and empathetic Artificial Intelligent (AI) agents who can deeply understand their users as unique individuals and responsibly guide their behavior in both virtual and real world. Starting with a live demo of showing how an AI interviewer chats with a user to automatically derive his/her personality characteristics and provide personalized recommendations, I will highlight the technical advances of the framework in two aspects. First, I will present a computational, evidence-based approach to Big 5 personality inference, which enables an AI agent to deeply understand a user's unique characteristics by analyzing the user's chat text on the fly. Second, I will describe a topic-based conversation engine that couples deep learning with rules to support a natural conversation and rapid customization of a conversational agent. I will describe the initial applications of our AI agents in the real world, from talent selection to student teaming to user experience research. Finally, I will discuss the wider implications of our work on building hyper-personalized systems and their impact on our lives.