The media are agog with claims that recent advances in AI put artificial general intelligence (AGI) within reach. Is this true? If so, is that a good thing? Alan Turing predicted that AGI would result in the machines taking control. At this lecture, presented as part of the Neubauer Collegium Director's Lecture series, Stuart Russell will argue that Turing was right to express concern but wrong to think that doom is inevitable. Instead, we need to develop a new kind of AI that is provably beneficial to humans. Unfortunately, we are heading in the opposite direction.

Following his talk, Russell will be joined in conversation with Rebecca Willett, Professor of Statistics and Computer Science at the University of Chicago and Faculty Director of AI at the Data Science Institute.

A livestream of this event will be available via Zoom.

About the Speakers

Stuart Russell is Professor (and formerly Chair) of Electrical Engineering and Computer Sciences and holder of the Smith-Zadeh Chair in Engineering at the University of California, Berkeley. He is co-chair of the World Economic Forum Council on AI and the OECD Expert Group on AI Futures, and he is a US representative to the Global Partnership on AI. His research covers a wide range of topics in artificial intelligence including machine learning, probabilistic reasoning, knowledge representation, planning, real-time decision making, multi-target tracking, computer vision, computational physiology, global seismic monitoring, and philosophical foundations. His textbook Artificial Intelligence: A Modern Approach (with Peter Norvig) is used in over 1,500 universities in 135 countries. His current concerns include the threat of autonomous weapons and the long-term future of artificial intelligence and its relation to humanity. The latter topic is the subject of his book Human Compatible: AI and the Problem of Control.

Rebecca Willett is Professor of Statistics and Computer Science at the University of Chicago and Faculty Director of AI at the Data Science Institute. Her research is focused on machine learning, signal processing, and large-scale data science.