Directions in Hybrid Intelligence: Complementing AI Systems with Human Intelligence

Historically, a common goal for the development of AI systems has been exhibiting intelligent behaviors that humans excel at. Consequently, most AI systems are designed to replace humans by completely automating well-defined tasks. Despite advances in AI, machines still have limitations in accomplishing tasks that come naturally to humans. In this talk, I will argue that our focus should not be in designing isolated AI systems, but instead we should focus on developing hybrid systems that combine the strengths of machine and human intelligence. I will provide an overview of our research efforts on how to integrate human intelligence into the training, execution and troubleshooting of AI systems. Next, I will summarize studies on understanding humans as helpers to AI systems and improving the interaction between humans and AI systems. I will conclude the talk by discussing opportunities and challenges in the development of hybrid systems.
Ece Kamar is a researcher at the Adaptive Systems and Interaction group at Microsoft Research Redmond. Ece earned her Ph.D. in computer science from Harvard University. While at Harvard, she received the Microsoft Research fellowship and Robert L. Wallace Prize Fellowship for her work on Artificial Intelligence. She has served as area chair and program committee member for various conferences on Artificial Intelligence and was a member of the first AI 100 panel, studying how Artificial Intelligence will affect the way we live. She works on several subfields of AI; including planning, machine learning, multi-agent systems and human-computer teamwork. She is passionate about combining machine and human intelligence towards developing real-world applications.