Events

Arrival: A Conversation with Denis Villeneuve and Dr. Nina Beguš

Event of Interest

MONDAY
November 1, 2026
David Geffen Theater

OSPO Monthly Meetup: Open source AI models

Event of Interest

THURSDAY 
15 October 2026
3:00 pm - 5:00 pm (Berkeley Time)
Gateway Building, Social Kitchen, Room 1420

Exhibition: “Hidden Layers: AI Infrastructures and Hallucinations”

Event of Interest

September 3rd - October 3
Worth Ryder Art Gallery, Anthropology & Art Building, Rm 116

Water and AI. What AI Can Learn from Water

Event of Interest

THURSDAY
1 October 2026
6:30 pm - 8:00 pm
Worth Ryder Art Gallery, Anthropology & Art Building, Rm 116

The Latent Spaces of Culture

Event of Interest

THURSDAY-SATURDAY
September 10-12, 2026
470 Stephens Hall

Co-designing Learning Technologies: With whom? For whom? For what?

HTF Colloquium

WEDNESDAY 
15 April 2026
3:00 pm - 4:00 pm (Berkeley Time)
Hearst Memorial Mining Building 390

Why do people’s use of technologies in everyday contexts often diverge drastically from their intended use, even after extended user feedback? How are educational technologies particularly prone to such divergences? Based on my experience with three large, multi-year NSF-funded projects that involved interdisciplinary research teams—spanning computer science, statistics, HCI, and education—I outline the affordances of collaborative design with potential users. I examine the norms and systems that interdisciplinary teams need to collectively learn from and respond to the co-design process. Read more...

Making Worlds in Novels and LLMs

HTF Colloquium

WEDNESDAY
8 April 2026
3:00 pm - 4:00 pm (Berkeley Time)
Hearst Memorial Mining Building 390

In what sense are the “worlds” of novels and of AI analogous, and what can each illuminate about the other? This talk argues that both novels and large language models (LLMs) construct worlds as networks of relations—patterns of events, inferences, and expectations—rather than as fully grounded causal systems. Read more...

What is Data Art?

HTF Colloquium

WEDNESDAY
1 April 2026
3:00 pm - 4:00 pm (Berkeley Time)
Hearst Memorial Mining Building 390

Based on historical data, predictive models such as the Kalman filter draw a cone of probable futures. But beyond ±3σ lie anomalies—floods, droughts, social ruptures, state changes—that statistics alone cannot contain. Imagination allows individuals and communities to inhabit these long tails together. It makes visible what the data implies but does not show, and enables the rehearsal of futures that differ from the past. Perhaps imagination is always social: a shared capacity to extend attention and care into futures the data alone cannot hold. Read more...

Computation as Critique: Adventures at the Limits of Spatial Data from the Pixel to the Pacific

HTF Colloquium

WEDNESDAY
11 March 2026
3:00 pm - 4:00 pm (Berkeley Time)
Hearst Memorial Mining Building 390

This talk treats computation as both a technical practice and a mode of inquiry, from the perspective of geographic critique of concepts such as space, place, and scale. Drawing on hands-on work in coding, geospatial analysis, and data infrastructure, I trace how spatial systems—from pixels and neural networks to GIS databases and web maps—shape how places are modeled, connected, and understood. I briefly situate my broader research in experimental cartography and critical data practice, then focus on computational work in the Pacific, where building and breaking island-level datasets reveals the assumptions embedded in spatial schemas and geographic hierarchies. Read more...

What Gets Encoded: AI, Inequity, and Alternative Technological Futures

HTF Colloquium

WEDNESDAY
4 March 2026
3:00 pm - 4:00 pm (Berkeley Time)
Hearst Memorial Mining Building 390

As AI is increasingly integrated across social and economic life, some of the most challenging problems sit at the boundary between computation and society. Chief among them are questions of fairness, equity, and bias: how these terms are defined and by whom, how they are encoded, and how we might build AI systems differently. This talk uses a sociotechnical lens grounded in Science and Technology Studies (STS) to investigate how inequity is built into AI as a “neutral” default and explores pathways toward alternative technological futures. Read more...