NYU AI School Wrapped: Democratizing AI Education
This June, CDS hosted its fourth annual NYU AI School, a week-long summer program that introduced artificial intelligence and machine learning to a diverse group of undergraduate students. The program, designed for those with little to no background in AI, attracted participants from fields as varied as psychology, computer science, biology, and the humanities.
NYU AI School, organized by members of the Machine Learning for Language (ML²) Lab, aimed to demystify AI for a broad audience. “Our goal was to make AI education accessible to students from all academic backgrounds, opening doors for those who might not typically have exposure to these cutting-edge technologies,” explained Divyam Madaan, a PhD student at NYU’s Courant Institute of Mathematical Sciences and one of the program organizers.
The program’s inclusivity was reflected in its diverse participant pool. Only 39% of attendees were computer science majors, with the rest coming from various disciplines. Remarkably, only 4% of participants were from NYU itself, with students attending from a wide range of colleges across the New York area.
To accommodate this diverse group, AI School offered two tracks: a programming track for those with coding experience and a non-programming track for complete beginners. The curriculum was carefully structured to provide a comprehensive introduction to AI. Madaan elaborated, “The first day was an overview of machine learning. People with no prior knowledge were given an introduction to what machine learning is, what to expect from the program, and what AI entails.”
The program progressed through a variety of important AI topics. “On the second day, we focused on computer vision, introducing students to how AI can interpret and analyze visual information,” Madaan explained. “The third day featured talks on natural language processing, showing how AI can understand and generate human language. For the final two days, we explored practical applications, with sessions covering AI’s role in neuroscience, climate science, and satellite imagery analysis.”
Elias Lemmel, a cognitive science student who attended the school, found the hands-on approach particularly valuable. “This school showed me how these AI models that everyone is talking about are implemented in code. Seeing how it actually looks when someone codes this was really helpful for grasping the concepts,” he said.
The program also included engaging panel discussions. “We incorporated two panel discussions this year, hand-picked for students just getting into AI,” Madaan explained. “One panel covered ‘Careers in AI’, providing insights into the various professional paths in the field. The other panel, ‘First Steps in ML’, offered practical advice for students looking to start their journey in machine learning.”.
Looking ahead, the organizers are already considering ways to enhance the program. Chastity Hidalgo, CDS Department Administrator and project manager for the school, reflected on the impact: “Interacting with participants and witnessing their enthusiasm made it clear there’s a real need and desire for this program going forward.”
As AI continues to permeate various aspects of our lives, programs like CDS’s NYU AI School play a crucial role in democratizing AI education. By providing accessible entry points for students from diverse backgrounds, the program is helping to shape a future where AI literacy is not limited to computer science graduates, but is a tool that can be wielded by thinkers and problem-solvers across all disciplines.
By Stephen Thomas
