Sam Gershman, Professor of Psychology at Harvard, discusses how we might build machines that learn and think like people, by combining insights from cognitive science, artificial intelligence, and computational neuroscience. Dr. Gershman elaborates on five key ingredients for a machine that learns and thinks like a person - intuitive physics, intuitive psychology, compositionality, learning-to-learn, and causality - reflecting on the importance of building more human-like machines and how close are contemporary AI systems to reaching this standard.

Video:

• Building machines that learn and think like people (28:21)

Additional Resources:

• Sam Gershman’s Lab website
• Lake, B. M., Ullman, T. D., Tenenbaum, J. B. & Gershman, S. J. (2017) Building machines that learn and think like people, Behavioral and Brain Sciences 40:e253.