Stephen Casper

Stephen Casper is a rising senior at Harvard College pursuing a degree in statistics and a minor in mathematics. In addition to interning at CHAI under Daniel Filan, he is affiliated with the MIT/Harvard Center for Brains, Minds, and Machines and the Harvard Kreiman Lab. Broadly, his research interests align with the goals of making AI systems safe and aligned. More specifically, areas that he is interested in include understanding compressible features and generalization in deep networks, robust reinforcement learning, and decision theory.

Stephen’s work with CHAI is focusing on mechanistic transparency via modular interpretations of neural networks. However, he is also thinking about adversaries in contexts of deep reinforcement learning and decision theory.

In addition to being fascinated by questions in machine intelligence, Stephen’s primary motivations for working on AI alignment involve using it as a strategy for shaping the future impactfully for the better. He is excited about the Effective Altruism community and the paradigm of maximizing the good that one can do in the world.

For more information and contact info, please see his website.