AI as a Window on Human Intelligence
- Speaker
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Matthew Botvinick, M.D., Ph.D.Senior Director of Research, DeepMind, and Honorary Professor, Gatsby Computational Neuroscience Unit, University College London
Presidential Lectures are a series of free public colloquia spotlighting groundbreaking research across four themes: neuroscience and autism science, physics, biology, and mathematics and computer science. These curated, high-level scientific talks feature leading scientists and mathematicians and are designed to foster discussion and drive discovery within the New York City research community. We invite those interested in these topics to join us for this weekly lecture series.
The last decade has seen explosive progress in artificial intelligence, with AI systems matching or exceeding human abilities in a rapidly growing range of settings. Current AI obviously has potentially transformative implications as technology. Perhaps less obvious are the opportunities it opens for gaining a deeper understanding of human intelligence.
In this talk, Matthew Botvinick will consider those opportunities. He will start with a review of the most relevant recent developments in AI and then describe recent studies in which innovations in AI have been translated into new insights concerning the human mind and brain.
About the Speaker
Botvinick is the senior director of research at DeepMind and an honorary professor at the Gatsby Computational Neuroscience Unit at University College London. Botvinick completed his undergraduate studies at Stanford University in 1989 and medical studies at Cornell University in 1994 before completing a Ph.D. in psychology and cognitive neuroscience at Carnegie Mellon University in 2001. He served as an assistant professor of psychiatry and psychology at the University of Pennsylvania until 2007 and a professor of psychology and neuroscience at Princeton University until joining DeepMind in 2016. His work at DeepMind straddles the boundaries between cognitive psychology, artificial intelligence and computational and experimental neuroscience.