Towards Building a Responsible Data Economy / Video / 作者: 編輯團隊 -NExT Forum：AI Security 詳細議程：https://www.hh-ri.com/forum/20220303.html -講者：Dawn Song, Dawn Song is a Professor in the Department of Electrical Engineering and Computer Science at UC Berkeley. Her research interest lies in AI and deep learning, security and privacy, and blockchain. She is the recipient of various awards including the MacArthur Fellowship, the Guggenheim Fellowship, the NSF CAREER Award, the Alfred P. Sloan Research Fellowship, the MIT Technology Review TR-35 Award, ACM SIGSAC Outstanding Innovation Award, and numerous Test-of-Time Awards and Best Paper Awards from top conferences in Computer Security and Deep Learning. She is an ACM Fellow and an IEEE Fellow. She is ranked the most cited scholar in computer security (AMiner Award). She obtained her Ph.D. degree from UC Berkeley. She is also a serial entrepreneur and has been named on the Female Founder 100 List by Inc. and Wired25 List of Innovators. -講題：Towards Building a Responsible Data Economy -摘要： In this talk, will talk about challenges and exciting new opportunities at the intersection of AI and Security,how AI and deep learning can enable better security, and how Security can enable better AI. In particular, will talk about secure deep learning and challenges and approaches to ensure the integrity of decisions made by deep learning. I will also give an overview on challenges and new techniques to enable privacy-preserving machine learning and responsible data use, towards building a platform for a responsible data economy. Finally, will conclude with future directions at the intersection of AI and Security.