CAIAC @ Collider
A summer paper club reading frontier research on AI safety, interpretability, and alignment science at Collider, NYC.
Apply nowEvery semester, CAIAC runs an 8-week introductory reading group on AI safety, covering topics like neural network interpretability¹, learning from human feedback², goal misgeneralization in reinforcement learning agents³, and eliciting latent knowledge⁴. This summer, CAIAC is running a paper club to read frontier research on AI safety, interpretability, and alignment science at Collider in Lower Manhattan.
See here for our Spring 2026 reading group curriculum (useful background for the reading group).
Past intro fellows have primarily been undergraduate, masters, and graduate students from Columbia. Because the summer session meets off-campus at Collider, you don't need to be affiliated with Columbia to join. In fact, we actively encourage you to apply if you're not affiliated with Columbia! One of the reasons we're holding this off-campus is so non-Columbia students can participate.
Participants should be familiar with basic concepts in machine learning, such as deep neural networks, stochastic gradient descent, and reinforcement learning. If you've previously gone through SPAR, CAMBRIA, or an introductory reading group at your university, you'll be in good shape. If you haven't but are technical, apply anyway!
The paper club meets once a week on Saturday for two hours, with brunch provided. We'll be meeting at Collider, the New York City home for AI safety, in Lower Manhattan.
The paper club is facilitated by CAIAC members and alumni with research experience in AI safety. This includes upperclassmen and graduates.