报告题目：Robust and Trustable AI with Human in the Loop
会 议 码：321-163-609
报 告 人：Prof. Tat-Seng CHUA
Dr. CHUA is the KITHCT Chair Professor at the School of Computing, National University of Singapore (NUS). He is also the Distinguished Visiting Professor of Tsinghua University, the Visiting Pao Yue-Kong Chair Professor of Zhejiang University, and the Distinguished Visiting Professor of Sichuan University. Dr. Chua was the Founding Dean of the School of Computing from 1998-2000. His main research interests include unstructured data analytics, video analytics, conversational search and recommendation, and robust and trustable AI. He is the co-Director of NExT, a joint research Center between NUS and Tsinghua University, and Sea-NExT, a joint Lab between Sea Group and NExT.
Dr CHUA is the recipient of the 2015 ACM SIGMM Achievements Award, and the winner of the 2022 NUS Research Recognition Award. He is the Chair of steering committee of Multimedia Modeling (MMM) conference series, and ACM International Conference on Multimedia Retrieval (ICMR) (2015-2018). He is the General Co-Chair of ACM Multimedia 2005, ACM SIGIR 2008, ACM Web Science 2015, ACM MM-Asia 2020, and the upcoming ACM conferences on WSDM 2023 and TheWebConf 2024. He serves in the editorial boards of three international journals. Dr. Chua is the co-Founder of two technology startup companies in Singapore. He holds a PhD from the University of Leeds, UK.
AI as a concept has been around since the 1950’s. With the recent advancements in machine learning technology, and the availability of big data and large computing resources, the scene is set for AI to be used in many systems and applications which will profoundly impact the society. The current deep learning based AI systems are mostly black box in nature and are often non-explainable. This has limited the applications of AI, especially in mission critical problems. This lecture focuses on robust and trustable AI, and the related research towards responsible computing.
The first part of this lecture examines the history of CS, and in particular AI, and discusses the new research paradigm that combines data driven and knowledge oriented AI towards a robust and trustable AI. The second part discusses the roles of humans in the AI eco-system, especially in solving the last-mile AI problems. The lecture covers recent research in incorporating AI and HITL (Human-in-the-Loop) into proactive information search and recommendation, multimodal conversation, and Fintech applications. The talk highlights the challenges of incorporating multimodal data and context in conversation, HITL, and the extensible and pro-active framework to enable the system and users to co-evolve and becoming more intelligent together.