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 human-AI interaction design and explainable AI research (XAI). But, why do some human-centered AI systems work, and some not? In this talk, I show how we can learn from human-human collaboration to design and build AI systems for human-AI collaboration. This work serves as a cornerstone towards the ultimate goal of Human-AI Collaboration, where AI and humans can take complementary and indispensable roles to achieve a better outcome and experience.
Dr. Wang will present in person.
Zoom: Virtual https://umd.zoom.us/j/98806584197?pwd=SXBWOHE1cU9adFFKUmN2UVlwUEJXdz09
(passcode if needed: clip)
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.