March 17th, Sunday | 9:30-10:45am | Pacific 1
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.
Dr. Michelle Zhou is a Co-Founder and CEO of Juji, Inc., an Artificial Intelligence (AI) startup located in Silicon Valley, specializing in building responsible and empathetic AI agents that can deeply understand users and guide their behavior based on their psychological characteristics. Prior to starting Juji, Michelle led the User Systems and Experience Research (USER) group at IBM Research – Almaden and then the IBM Watson Group. Michelle’s expertise is in the interdisciplinary area of intelligent user interaction (IUI), including conversational systems and personality analytics. She has published over 100 peer-reviewed, refereed articles and filed over 40 patents. Michelle is currently the Editor-in-Chief of ACM Transactions on Interactive Intelligent Systems (TiiS) and an Associate Editor of ACM Transactions on Intelligent Systems and Technology (TIST). She received a Ph.D. in Computer Science from Columbia University and is an ACM Distinguished Scientist.
March 18th, Monday | 8:30-9:45am | Sierra I & II
Dramatic success in machine learning (ML) has led to a new wave of artificial intelligence (AI) applications (e.g., transportation, security, medicine, finance, and defense) that offer tremendous benefits, but cannot explain their decisions and actions to human users. DARPA’s Explainable Artificial Intelligence (XAI) program endeavors to create AI systems whose learned models and decisions can be understood and appropriately trusted by end users. Realizing this requires methods for learning more explainable models, designing effective explanation interfaces, and understanding the psychological requirements for effective explanations. XAI’s developer teams are addressing the first two challenges by creating ML techniques and developing principles, strategies, and human-computer interaction techniques for generating effective explanations. Another XAI team is addressing the third challenge by summarizing, extending, and applying psychological theories of explanation to assist the XAI evaluator with defining a suitable evaluation framework, which the developer teams will use to test their AI systems. XAI completed the first phase of the program in February 2019. During this phase, each developer team conducted a user evaluation to assess their AI system’s ability to improve user understanding, trust, and user task performance. This talk will summarize the XAI program and present highlights from these Phase 1 evaluations.
David Gunning is DARPA program manager in the Information Innovation Office (I2O). Dave has an over 30 years of experience in the development of artificial intelligence (AI) technology. At DARPA, Dave manages the Explainable AI (XAI) and the Communicating with Computers (CwC) programs. This is Dave’s 3rd tour as a DARPA PM. Previously, Dave managed the Personalized Assistant that Learns (PAL) project that produced Siri and the Command Post of the Future (CPoF) project that was adopted by the US Army as their Command and Control system for use in Iraq and Afghanistan. In between DARPA tours, Dave was a Program Director for Data Analytics at the Palo Alto Research Center (PARC), a Senior Research Manager at Vulcan Inc., SVP of SET Corp., VP of Cycorp, and a Senior Scientist in the Air Force Research Labs. Dave holds a M.S. in Computer Science from Stanford University, a M.S. in Cognitive Psychology from the University of Dayton, and a B.S. in Psychology from Otterbein College.
March 19th, Tuesday | 9:00-10:15am | Sierra I & II
Google has created 8 products with over a billion users each. These products are powered by AI (artificial intelligence) at every level —from the core infrastructure and software platform to the applica-tion logic and the user interface. I’ll share a behind-the-scenes look at how Google AI works and how we use it to create innovative UX (user experience) at a planetary scale. I’ll end with our vision to democratize AI and how you can use Google AI in your own work.
Ashwin Ram is Technical Director of AI in the Office of the CTO for Google Cloud. He focuses on bringing Google AI to the world through deep personalized engagement with the leadership of top companies to reimagine their businesses by leveraging the power of AI. He also works with Google’s AI teams to drive new technologies and capabilities that address customer needs. Ashwin is a distinguished AI researcher, technologist, and entrepreneur. Prior to Google, Ashwin was Senior Manager of AI Science for Amazon Alexa. He led cross-functional R&D initiatives to create advanced Conversational AI technologies for intelligent agents, including the university-facing Alexa Prize competition. Earlier, Ashwin was a professor at Georgia Tech, co-founded 4 startups, and managed the Interactive Intelligence area at Xerox PARC. He received his PhD from Yale University in 1989, his MS from University of Illinois in 1984, and his BTech from IIT Delhi in 1982. He has published 2 books and over 100 scientific articles in international forums.