Dr. Samuel Gershman is a Professor of Psychology at Harvard University, where he directs the Computational Cognitive Neuroscience Laboratory. He is also the author of What Makes Us Smart: The Computational Logic of Human Cognition.

In this episode we discuss Sam’s book, and the central argument that human brains are computers that must operate based on both limits of information and limits of computational power. These limits are what lead to biases, but Sam stresses that biases in human cognition, such as falling for optical illusions, are in fact what make us smart. We talk about some of the mechanisms by which we learn, such as statistical learning, and discuss the similarities and differences between human learning and modern artificial intelligence. We also discuss some of Sam’s theoretical research on the computational and neural mechanisms involved in learning and memory, and discuss how this model may apply to animals as simple and diverse as small planarian flatworms.