Michiel Bakker (Cancelled)

Title

The Habermas Machine: AI can help humans find common ground in democratic deliberation

Abstract

Collective deliberation is crucial for resolving complex societal issues, yet traditional methods are slow, difficult to scale, and often struggle to equitably represent diverse perspectives. In this talk, I will present a project that was published in Science last October in which we use large language models (LLMs) to facilitate consensus-building. Our system iteratively synthesizes participants' personal opinions and critiques to generate statements that capture common ground on contentious topics. Across multiple studies, including a virtual citizens' assembly with a demographically representative UK sample, participants rated AI-mediated deliberations as more informative, clear, and unbiased than human-written alternatives. Notably, discussants often revised their views post-deliberation, converging on a shared perspective. Beyond these results, I will explore how AI-mediated deliberation informs broader efforts in pluralistic AI alignment, ensuring AI systems can navigate and respect diverse human values rather than imposing a singular perspective. I will also discuss how these techniques apply to real-world sociotechnical systems like X Community Notes, where AI helps identify broadly supported insights in a real-world crowdsourced fact-checking system.

Bio

Michiel Bakker is an Assistant Professor at MIT Sloan, with affiliations in the Institute for Data, Systems, and Society (IDSS) and the Center for Constructive Communication (CCC) in the MIT Media Lab. He is also a Senior Research Scientist at Google DeepMind. His research focuses on AI alignment, collective decision-making, and the societal impacts of AI. Previously, he completed a PhD and master’s in Computer Science at MIT and a bachelor’s and master’s in Physics from TU Delft, where he worked on quantum computing at QuTech and IBM Quantum.

Zoom link: https://northwestern.zoom.us/s/93709486243