세미나 제목: Human Helping Machine Helping Human: Building Hybrid Intelligent Systems to Improve Human-Machine Collaboration

세미나 초록: With the rapid development of both software and hardware technologies for the last decade, various AI-infused systems are now available for users in real life. However, despite the popular usage, there are many remaining challenges including usability, safety, reliability, robustness, accountability, transparency, fairness, and many more. For better usage of AI-infused systems, both interactions between systems and developers and between systems and users must be considered from the design stage. This is because understanding and designing the interactions in a way to improve collaborative performance of human and machine can not only help build better AI-infused systems, but also enable to achieve things that exceed what either can do alone. This talk introduces studies implementing human-machine hybrid systems and discusses how these studies can make AI services more useful and secure.

BIO: Jean Young Song is an Assistant Professor at the Department of Information and Communication Engineering at DGIST. She received her Ph.D. degree in Electrical Engineering and Computer Science at the University of Michigan in 2019, and B.S. and M.S. degrees in Electrical and Electronic Engineering at Yonsei University in 2009 and 2011. Before joining DGIST, she worked as a Research Assistant Professor in the School of Computing at KAIST. Her primary research area is human-computer interaction (HCI), human-AI interaction, and crowdsourcing, where she develops techniques to more efficiently and accurately collect machine learning datasets for computer vision and natural language processing. The main goal of her research is to apply HCI methodologies to solve challenging and interesting AI problems. She received many best paper awards including ACM IUI (2018), ACM CSCW (2019), ACM AAMAS (2020), and ACM IUI (2021).