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October 7, 2022 Dakuo Wang of MIT-IBM Watson AI Lab Human-Centered AI (HCAI) refers to the research effort that aims to design and implement AI techniques to support various human tasks, while taking human needs into consideration and preserving human control. Prior work has focused on proposing human-AI interaction design guidelines and explainable AI (XAI) methods, but, why do some human-centered AI systems work, and some still not in the real world? In this talk, I show how we can learn from the research about human-human collaborations to guide the design and development of AI systems for a human-AI collaboration paradigm. This series of works serves as a cornerstone towards the ultimate future of Human-AI Collaboration, where AI and humans can take complementary and indispensable roles, and together to achieve a better experience and outcome and experience. About the speaker: Dakuo Wang is a Research Staff Member at IBM Research, Principal Investigator at MIT-IBM Watson AI Lab, and Adjunct Professor at Northeastern University. His research lies at the intersection of human-computer interaction (HCI), artificial intelligence (AI), and computer-supported team collaboration (CSCW), with a focus on the exploration, development, and evaluation of human-centered AI (HCAI) systems. The overarching research goal is to democratize AI for every person and every organization, so that they can easily access AI and collaborate with AI to accomplish real-world tasks better -- the human-AI collaboration paradigm. Before joining IBM Research, Dakuo got his Ph.D. from the University of California Irvine (how people write together now co-advised by Judith Olson and Gary Olson). He has worked as a designer, researcher, and engineer in the U.S., China, and France. He has served in various organizing committees, program committees, and editorial boards for conferences and journals, and ACM has recognized him as an ACM Distinguished Speaker. #hci