Upcoming: Critical AI Graduate Conference
On Tuesday, March 11th, from 3-6pm, the Center for the Humanities and Machine Learning will host a graduate conference, featuring presentations by participants in Co-Director Fabian Offert's "Critical Theory and/of Artificial Intelligence" graduate seminar. All are welcome to attend.
View details on our Events page
Recap: HUML Launch Event
Our launch event with Hannes Bajohr, Assistant Professor of German at UC Berkeley, brought together faculty, administrators, and graduate students from across UCSB. Bajohr's keynote, titled "Surface Reading LLMs: Synthetic Text and its Styles," inspired lively discussion of aesthetics, interpretation, and intersubjectivity.
Save the Date: HUML Launch Event with Hannes Bajohr
Mark your calendars for the inaugural HUML event on Friday, January 24th. Hannes Bajohr (German, UC Berkeley) will deliver a keynote and Q&A titled "Surface Reading LLMs: Synthetic Text and its Styles." HUML Co-Directors Fabian Offert (German & Slavic Studies/Comparative Literature) and Rita Raley (English) will also discuss their upcoming book projects, on image and language models, respectively, followed by a reception with light refreshments. We hope to see you there!
View details on our Events page
Report: The 2024 Critical AI Funding Landscape
This report, prepared by graduate researcher Owen Leonard, provides an overview of Critical Artificial Intelligence funding in the United States—from major academic research initiatives to community-center workshops. Leonard emphasizes the need for research that examines the social and political possibilities of AI, both positive and negative, and offers recommendations for researchers to maximize relevance and impact.
Interview: Fabian Offert and Rita Raley on Critical Machine Learning
Read an interview with Co-PIs Fabian Offert and Rita Raley on the 2023 Critical Machine Learning Studies working group, which helped develop the ideas behind HUML. Offert and Raley articulate a "critical ML" approach from within Critical AI studies that foregrounds the material basis of computational technology and questions the utility of "AI" as a convenient but imprecise abstraction.
Check out the interview transcript