CS Talk
Sarah Cen
Host: Manolis Zampetakis
Title: Paths to AI Governance
Abstract:
We have begun grappling with difficult questions related to the rise of AI, including: What rights do individuals have in the age of AI? When should we regulate AI and when should we abstain? What degree of transparency is needed to monitor AI systems? These questions are all concerned with AI governance. In this talk, I discuss the three main components of AI governance, then illustrate them through a case study on auditing social media.
Within the context of social media, I will focus on how social media platforms filter (or curate) the content that users see. In particular, I will propose a way to implement regulations on social media that is compatible with free speech protections and Section 230. I will then present a way to test whether a content curation algorithm complies with regulations, producing what we call a “counterfactual audit.” In studying the properties of this approach, I will show that it has strong theoretical guarantees, does not violate user privacy, and uses only black-box access to the algorithm (thereby requiring minimal access to proprietary algorithms and data). I will demonstrate how this audit can be applied in practice using LLMs on a live social media platform.
Bio:
Sarah is a final-year PhD student at MIT in the Electrical Engineering and Computer Science Department advised by Professor Aleksander Mądry and Professor Devavrat Shah. Sarah utilizes methods from machine learning, statistical inference, causal inference, and game theory to study responsible computing and AI policy. Previously, she has written about social media, trustworthy algorithms, algorithmic fairness, and more. She is currently interested in AI auditing, AI supply chains, and the intellectual property (IP) rights of data providers.