CHAI's mission is to develop the conceptual and technical wherewithal to reorient the general thrust of AI research towards provably beneficial systems.
These videos introduce some of the problems that we work on.
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A recent New Scientist article features a paper that Tom Griffiths and Stuart Russell wrote along with David D. Bourgin, Joshua C. Peterson, and Daniel Reichman. The article discusses how the researchers were able to make a machine learning model that took into account human biases, like risk adversion, that are usually hard for computer systems to model.
CHAI faculty and graduate students presented their papers at the latest International Conference on Machine Learning.
CHAI researchers Michael Dennis, Adam Gleave, Cody Wild, Neel Kant, and Stuart Russell, along with Sergey Levine, gave a talk on their paper Adversarial Policies: Attacking Deep Reinforcement Learning at the International Conference on Machine Learning 2019. There is a video of the talk on the ICML Github (starts at 1h:35m) and the slides can be here
Michael Littman, a professor at Brown University, recently gave a talk at CHAI on Reward Design for Cooperation. Professor Littman also runs the Humanity-Centered Robotics Initiative with Bertram Malle and Peter Haas.
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