Understanding AI: Humanities × Social Sciences × Technology

Organized by UC Berkeley Social Science Matrix and co-sponsored by the School of Information.

Understanding and interpreting AI is the new frontier in AI research. While advances in the performance of AI models have seen enormous successes, a profound understanding of how learning happens inside the models remains to be thoroughly explored.

Understanding how AI learns has the potential to help us gain novel insights in science, technology, and other fields, as well as to observe novel causal relationships in various types of data. Interpreting the internal workings of AI models can also shed light on how the human mind works and how we are similar to and different from machines. 

The answers to these questions have highly consequential implications across disciplines, which is why it is imperative for scholars from a variety of fields to come together and collaborate. Our symposium represents a step towards fostering these interdisciplinary discussions. We will  identify immediate challenges in AI interpretability and explore how the humanities, social sciences, and the tech world can join forces in this highly consequential research.

This event will also be live streamed on Zoom.

Register

Panelists

Joshua Batson
AnthropicAI

Gašper Beguš
Assistant Professor of Computational Linguistics
UC Berkeley
Project CETI

Benjamin Bratton
Professor of Philosophy of Technology and Speculative Design
UC San Diego
Director of the Berggruen Institute’s Antikythera

Dawn Song
Professor at EECS
UC Berkeley

Claire Webb
Director
Berggruen Institute’s Future Humans