The problem of intelligence – its nature, how it is produced by the brain and how it could be replicated in machines – is a deep and fundamental problem that cuts across multiple scientific disciplines. Philosophers have studied intelligence for centuries, but it is only in the last several decades that developments in a broad range of science and engineering fields have opened up a thriving “intelligence research” enterprise, making questions such as these approachable: How does the mind processes sensory information to produce intelligent behavior, and how can we design intelligent computer algorithms that behave similarly? What is the structure and form of human knowledge – how is it stored, represented and organized? How do human minds arise through processes of evolution, development and learning, and what are their roots in genetics? How does collective intelligence arise in social and economic systems? How are cognitive domains including language, perception, social cognition, planning and motor control combined and integrated? Are there common principles of learning, prediction, decision or planning that span across different domains?

The second iteration of this course will explore these issues with an approach that involves the integration of the fields of cognitive science, which studies the mind, neuroscience, which studies the brain, and computer science and artificial intelligence, which develop intelligent hardware and software. Each week, different faculty members will lecture on a research topic that relates to the problem of intelligence. This year speakers will complement last year’s lectures. The class will also consist of readings, discussion, and individual or group projects.

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