Unsupervised Pleasures: Intersectional Language Models for Queer Futures
08-16, 10:45–11:45 (Europe/Berlin), Digitalcourage
Language: English

What does GPT-4 know about people like me? This interactive workshop peeks under the hood of large language models to understand what goes into the datasets that shape them. We will discuss how these giant text corpora represent us in ways that feel hollow, harmful, and incomplete. I will share my analysis of existing datasets in an artistic research context, plus collaborative research that proposes building alternative models, methods, and datasets featuring texts that orient toward life and liberation. These texts will include, but not be limited to, works that center decolonial perspectives, queer love, ethics of care, and practices of commoning and mutual aid--created with transparency, community input, and contributor consent. Our collective Unsupervised Pleasures is developing more intersectional machine learning methodologies, and in our discussion we will unpack the issues with existing tools and imagine different tools that can support the communities they represent instead. Are these the automated systems we want? Whose voices, visions, and stories are captured in them and whose are excluded, harmed, or undermined? Let’s start building the language tools we want to see in the world.

Open to any level of technical knowledge, from zero to expert. All backgrounds welcome!

Content Notes

Discusses LGBTQIA+ identities, race, gender, and treatment of these topics in automated systems. Will include some problem examples of racism, misogyny, homophobia. However, discussion will primarily focus on how communities can provide counternarratives for themselves.

Sarah Ciston builds critical–creative tools to bring Intersectional approaches to machine learning. Recently named “AI Newcomer” by the German Informatics Society, they are an AI Anarchies Fellow with the Akademie der Künste, a Mellon Fellow in Media Arts and Practice at the University of Southern California, and an Associated Researcher at the Humboldt Institute for Internet and Society, plus author of “A Critical Field Guide to Working with Machine Learning Datasets” from the Knowing Machines research project. Sarah’s projects include an interactive NLP database to "rewrite" the inner critic and a bot that tries to explain feminism to online misogynists. They lead Creative Code Collective, a student community for co-learning programming using approachable, interdisciplinary strategies.