Inside AI's Hidden Supply Chain

AI systems are no longer just individual models trained and deployed in isolation. Today’s production systems increasingly combine models, datasets, APIs, agents, harnesses, and services—often spanning multiple organizations—into complex AI supply chains. In this video, MIT CSAIL researchers Aspen Hopkins and Professor Aleksander Mądry discuss why this shift changes how we need to deploy or govern AI. Reliable components do not automatically produce a reliable system, and an upstream change can have unexpected downstream effects. How can a systems-of-systems perspective help uncover current gaps in tooling—and what new approaches will we need? Related research: AI Supply Chains: An Emerging Ecosystem of AI Actors, Products, and Services Aspen Hopkins*, Sarah H. Cen*, Andrew Ilyas, Isabella Struckman, Luis Videgaray, and Aleksander Mądry When Should Model Updates Propagate? Aspen Hopkins, Isabella Struckman, Hedi Driss, and Aleksander Mądry Link coming soon! Director: Rachel Gordon Image & Edit: Tim Malieckal Script Supervisor: Alex Shipps