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 interface design and explainable AI research (XAI). However, despite these fruitful research results, why do many so-called “human-centered” AI systems still fail in the real world? In this talk, I will discuss the human-AI interaction paradigm, and show how we can learn from human-humancollaboration to design and build AI systems that lead to a successful interaction paradigm, especially in this LLM era. 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.

About the speaker
Dr. Dakuo Wang is an Associate 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 collaboratewith AI to accomplish real-world tasks better — the “human-AI collaboration” paradigm. Before joining Northeastern, Dr.Wang worked as a research lead at IBM Research, and a principal investigator at MIT-IBM Watson AI Lab. He 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.