What we see and what we value: AI with a human perspective
Fei-Fei Li (Stanford University)
Distinguished Lecture
Thursday, January 18, 2024, 3:30 pm
Abstract
One of the most ancient sensory functions, vision emerged in prehistoric animals more than 540 million years ago. Since then animals, empowered first by the ability to perceive the world, and then to move around and change the world, developed more and more sophisticated intelligence systems, culminating in human intelligence. Throughout this process, visual intelligence has been a cornerstone of animal intelligence. Enabling machines to see is hence a critical step toward building intelligent machines. In this talk, I will explore a series of projects with my students and collaborators, all aiming to develop intelligent visual machines using machine learning and deep learning methods. I begin by explaining how neuroscience and cognitive science inspired the development of algorithms that enabled computers to see what humans see. Then I discuss intriguing limitations of human visual attention and how we can develop computer algorithms and applications to help, in effect allowing computers to see what humans don't see. Yet this leads to important social and ethical considerations about what we do not want to see or do not want to be seen, inspiring work on privacy computing in computer vision, as well as the importance of addressing data bias in vision algorithms. Finally I address the tremendous potential and opportunity to develop smart cameras and robots that help people see or do what we want machines’ help seeing or doing, shifting the narrative from AI’s potential to replace people to AI's opportunity to help people. We present our work in ambient intelligence in healthcare as well as household robots as examples of AI's potential to augment human capabilities. Last but not least, the cumulative observations of developing AI from a human-centered perspective has led to the establishment of Stanford's Institute for Human-centered AI (HAI). I will showcase a small sample of interdisciplinary projects supported by HAI.
Bio
Dr. Fei-Fei Li is the inaugural Sequoia Professor in the Computer Science Department at Stanford University, and Co-Director of Stanford’s Human-Centered AI Institute. She served as the Director of Stanford’s AI Lab from 2013 to 2018. And during her sabbatical from Stanford from January 2017 to September 2018, Dr. Li was Vice President at Google and served as Chief Scientist of AI/ML at Google Cloud. Since then she has served as a Board member or advisor in various public or private companies.
Dr. Fei-Fei Li obtained her B.A. degree in physics from Princeton in 1999 with High Honors, and her PhD degree in electrical engineering from California Institute of Technology (Caltech) in 2005. She also holds a Doctorate Degree (Honorary) from Harvey Mudd College.
Dr. Fei-Fei Li’s current research interests include cognitively inspired AI, machine learning, deep learning, computer vision, robotic learning, and AI+healthcare especially ambient intelligent systems for healthcare delivery. In the past she has also worked on cognitive and computational neuroscience. Dr. Li has published more than 300 scientific articles in top-tier journals and conferences in science, engineering and computer science. Dr. Li is the inventor of ImageNet and the ImageNet Challenge, a critical large-scale dataset and benchmarking effort that has contributed to the latest developments in deep learning and AI. In addition to her technical contributions, she is a national leading voice for advocating diversity in STEM and AI. She is co-founder and chairperson of the national non-profit AI4ALL aimed at increasing inclusion and diversity in AI education.
Dr. Li has been working with policymakers nationally and locally to ensure the responsible use of technologies, including a number of U.S. Senate and Congressional testimonies, her service as a special advisor to the Secretary General of the United Nations, a member of the California Future of Work Commission for the Governor of California in 2019 - 2020, and a member of the National Artificial Intelligence Research Resource Task Force (NAIRR) for the White House Office of Science and Technology Policy (OSTP) and the National Science Foundation (NSF) in 2021-2022.
Dr. Li is an elected Member of the National Academy of Engineering (NAE), the National Academy of Medicine (NAM) and American Academy of Arts and Sciences (AAAS). She is also a Fellow of ACM, a member of the Council on Foreign Relations (CFR), a recipient of the Intel Lifetime Achievements Award in 2023, a recipient of the 2022 IEEE PAMI Thomas Huang Memorial Prize, 2019 IEEE PAMI Longuet-Higgins Prize, 2019 National Geographic Society Further Award, IAPR 2016 J.K. Aggarwal Prize, the 2016 IEEE PAMI Mark Everingham Award, the 2016 nVidia Pioneer in AI Award, 2014 IBM Faculty Fellow Award, 2011 Alfred Sloan Faculty Award, 2009 NSF CAREER award, the 2006 Microsoft Research New Faculty Fellowship, among others. Dr. Li is a keynote speaker at many academic or influential conferences, including the World Economics Forum (Davos), the Grace Hopper Conference 2017 and the TED2015 main conference. Work from Dr. Li's lab have been featured in a variety of magazines and newspapers including New York Times, Wall Street Journal, Fortune Magazine, Science, Wired Magazine, MIT Technology Review, Financial Times, and more. She was selected as a 2017 Women in Tech by the ELLE Magazine, a 2017 Awesome Women Award by Good Housekeeping, a Global Thinker of 2015 by Foreign Policy, and one of the “Great Immigrants: The Pride of America” in 2016 by the Carnegie Foundation, past winners include Albert Einstein, Yoyo Ma, Sergey Brin, et al.
Dr. Fei-Fei Li is the author of the book "The Worlds I See: Curiosity, Exploration and Discovery at the Dawn of AI", published by Macmillan Publishers in 2023.
This talk is available on the Allen School's YouTube channel.