This summer, the MIT Schwarzman College of Computing welcomed faculty from colleges and universities across Greater Boston, South Carolina, West Virginia, and Texas to campus for the inaugural AI Educators Pilot, a weeklong workshop aimed at expanding how artificial intelligence is taught across disciplines and learning environments. 

Inspired by MIT class C01/C51 (Modeling with Machine Learning), a course developed through the Common Ground for computing and AI education that focuses on helping students understand and apply foundational AI and machine learning concepts to problem-solving in their own disciplines, the workshop gave educators an opportunity to explore how its materials and teaching methods could be adapted for their classrooms. 

“The broader goal is to expand AI education to more students by investing in training for instructors,” says Dan Huttenlocher, dean of the MIT Schwarzman College of Computing and the Panasonic Professor of Electrical Engineering and Computer Science (EECS).

“We want to empower students to become critical thinkers about AI, not just users of the technology,” says Asu Ozdaglar, deputy dean of academics for the MIT Schwarzman College and department head of EECS.

Bringing the program to life required broad collaboration across the college, including support from leadership, staff, and contributions from more than half a dozen instructors in fields ranging from finance and computer science to sustainability. Together, they helped shape a workshop that paired core technical concepts with examples and teaching materials adaptable to a range of classroom settings.

“I have not seen an effort quite like it — this many dedicated instructors assembling materials of this richness, all to equip the educators who serve their students,” says Saurabh Amin, the Edmund K.

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