Two departments team up to study human and artificial intelligence

A new joint major combines human cognition, neuroscience, and computer science.

Department of Electrical Engineering and Computer Science | Department of Brain and Cognitive Science

As human brains increasingly interact with technology that mimics their own capabilities, the need for students to understand both the science and engineering of intelligence continues to grow as well. At the same time, ongoing advances in these technologies are driving demand for a deeper understanding of how the brain works.

In response, EECS and the Department of Brain and Cognitive Sciences (BCS) have teamed up to offer a new joint degree. The bachelor of science in computation and cognition (Course 6-9), approved by the faculty in April 2019, is designed to help students explore how the brain produces intelligent behavior and how it can be replicated in machines. Launched in September 2019, the new major now enrolls about 40 students.

“The 6-9 major fulfills a growing educational need at the intersection of cognitive science, neuroscience, and computer science,” says James DiCarlo, BCS department head and the Peter de Florez Professor of Neuroscience. “It is a forward-thinking step that embraces a dynamic new field of research that our faculty and students have shown great interest in. It’s an incredibly exciting time for students to be educated in the foundations of these efforts and to participate in shaping the future of the science and engineering of intelligence.”

Both DiCarlo and EECS department head Asu Ozdaglar noted that 6-9 also reflects Institute-wide enthusiasm for interdisciplinary initiatives such as the Quest for Intelligence and the new MIT Stephen A. Schwarzman College of Computing. “The new joint major also builds on an already strong relationship between our two departments. Ultimately, it will create a new community of graduates who are uniquely qualified to tackle cutting-edge research questions in this exciting emerging field,” says Ozdaglar, the School of Engineering Distinguished Professor of Engineering.

Anyone seeking to do novel research in artificial intelligence (AI) or machine learning will find it helpful to know “both how machines work and how humans make decisions and learn,” says Dennis M. Freeman, the Henry Ellis Warren (1894) Professor of Electrical Engineering and EECS education co-officer. “Both perspectives are critical to transformational advances.”

“There’s a lot of shared interest around emerging new fields at the intersection of AI and cognitive science and of machine learning and brain science,” says Michale S. Fee, the Glen V. (1946) & Phyllis F. Dorflinger Professor of Neuroscience and the associate department head for education in BCS. “There is a lot of synergy between those areas, and advances would be facilitated by the cross-fertilization of ideas.”

The new course of study recognizes the explosion of interest in topics at the intersection of the two departments. “We’ve always had students in EECS interested in cognitive sciences and vice versa,” Freeman says. “Recently, these have become the growth areas in both of our departments.” For example, he notes, nearly 500 students enrolled in 6.036 (Introduction to Machine Learning) in the spring of 2019.

The new major is expected to attract about 50 students annually, based on a survey of students already enrolled in BCS subjects focused on human cognition and computation, such as 9.66 (Computational Cognitive Science). “This is a substantial number, if it materializes — and we have every reason to think it will,” Fee says.

“There’s a big commercial push for these skills,” Freeman adds, noting that many of the methods used to help computers conduct “thinking” tasks — such as recognizing faces, driving cars, and even diagnosing diseases — are based on knowledge obtained studying humans.

At the same time, it’s also increasingly important for neuroscientists to have computational skills, Fee says. “One of the really transformative things that’s happening in brain science is that new technologies and methods are creating enormous data sets,” he says. One example: It’s now possible to record the activity of hundreds of thousands of neurons. “These are incredibly huge data sets, and the best way to analyze them is to use artificial intelligence. We’re basically building artificial brains to analyze the data in order to figure out how the human brain works,” he says.

The new major will equip students to take on advanced subjects in EECS; the architecture, circuits, and physiology of the brain; and computational approaches to cognition and intelligence. To provide a foundation for these academic pathways, 6-9 majors will be required to take both 6.0001 (Introduction to Computer Science Programming in Python) and 9.01 (Introduction to Neuroscience), as well as a foundational math class. They will also have to complete a senior-level, project-based class.

“One of the challenges we faced was how to combine these two disciplines into a flexible program,” Fee says. “I think we’ve got a really great curriculum that provides that flexibility.”

Freeman says the new major should prove a boon for students who might otherwise have double-majored in EECS and BCS, because few of the requirements of established majors overlap. For that reason, students should have more freedom to choose electives from options such as 6.021J/9.21J (Cellular Neurophysiology and Computing), 9.35 (Perception), 9.19 (Computational Psycholinguistics), and 9.40 (Introduction to Neural Computation).

Last May, the faculty also approved an associated master of engineering (MEng) degree. Students wishing to pursue that degree would need to take six additional subjects, conduct lab research in either Course 6 or 9, and write a master’s thesis. “We think that master’s will be a great opportunity for students who want to get advanced training to be more competitive for employment either in industry or for graduate study,” Fee says.

This is the fourth EECS-related joint degree program launched in recent years. The first, Course 6-7 (Computer Science and Molecular Biology), launched in 2012, followed by Course 6-14 (Computer Science, Economics, and Data Science) in 2017 and 11-6 (Urban Science and Planning with Computer Science) last fall. The 6-9 major will jointly reside in EECS and BCS, and enrolled students will have a primary academic advisor in BCS with a secondary advisor in EECS.

For more information about Course 6-9, students should contact Jillian Auerbach in BCS and the undergraduate office in EECS.

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