Workshop: A generative disaster, Algorithmic creativity and climate futures

The sizeable impact of AI on our environment is increasingly understood to be a point of concern. Not just our physical environments, but our digital environments too are ‘polluted’ by AI generated slop: lethal recipes, nonsensical podcasts, inaccurate images of baby peacocks etc.

Workshop

In this workshop we set out to cultivate this environment more intentionally. What if we explored the potential of generative AI for the propagation of climate futures that wedge open the plausible, to reveal instead futures that are weird or desirable, and thus impactful in their potential to un-stick us from our committed course of action? 

In this workshop we will perform a series of group-based exercises, critically co-creating with AI models to learn:

1. How to approach LLMs as ‘field sites';
2. How AI storytelling compares to algorithmic storytelling using analog ttrpg ‘engines’ 
3. How gen AI may be used creatively to break up the ‘hegemonologue.

Running the workshop are: Gabriele de Seta, digital folklorist and ‘synthetic ethnographer’ from Bergen University (NO ) - PI of Algofolk, and Laura op de Beke, Assistant Professor of Interactive Media.

Lecture

Those interested in the qualitative study of LLMs may also want to join for Gabriele de Seta’s lecture on Algorithmic Creativity and Synthetic Ethnography, from 13.00-14.00 at the same venue (Muntstraat 2A, Grote Zaal). De Seta is a sociologist and digital folklorist at the University of Bergen, where he leads the ALGOFOLK project (“Algorithmic folklore: The mutual shaping of vernacular creativity and automation”). 

In this talk, Dr. de Seta traces a critical history of generative AI and the shifting concept of creativity in computational contexts. From early algorithmic art to today’s large language models, he explores how our cultural imaginaries and technical infrastructures co-produce the notion of creative machines. The lecture also introduces synthetic ethnography—an experimental set of qualitative methods for researching AI systems using AI systems themselves. 

Drawing from recent work at the intersection of digital anthropology and critical data studies, Dr. de Seta reflects on how ethnographers might engage large language models as both field sites and collaborators