The impossible image describes the botanical illustrations crucial to building the British Empire, and the ways botanical drawings emerged as a moral model. In this talk, Wang will draw the connections between the impossible image of botanical illustrations and the traces of the impossible image in current understandings of generative AI. In this unpacking, Wang will look at these traces and their relation to biocentric ways of thinking, as well as at constructions and models of humanness and the body.
Xiaowei R. Wang is an artist, writer, organizer, and coder. They are the author of the book Blockchain Chicken Farm: And Other Stories of Tech in China’s Countryside, a 2023 National Book Foundation Science and Literature Award winner. Their writing has appeared in TANK, transmediale, The Nation, and more. Currently, they are one of the stewards of Logic School, an organizing community for tech workers, as well as a Research Fellow at the Center on Race and Digital Justice and a Senior Civic Media Fellow at USC Annenberg. They are working on their second book on the design of tech for care, as well as a new body of work, Witch Fever, that is a speculative botany co-created with an AI.
Lecture Series 2022-23
A model can be an object of admiration, a miniature or a prototype, an abstracted phenomenon or applied theory, a literary text — practically anything from a human body on a catwalk to a mathematical description of a system. It can elicit desire, provide understanding, guide action or thought. Despite the polysemy of the term, models across disciplines and fields share a fundamental characteristic: their effect depends on a specific relational quality. A model is always a model of or for something else, and the relation is reductive insofar as it is selective and considers only certain aspects of both object and model.
Critical discussions of models often revolve around their restrictive function. And yet models are less prescriptive and more ambiguous than codified rules or norms. What is the critical purchase of models and how does their generative potential relate to their constitutive reduction? What are the stakes in decreasing or increasing, altering or proliferating the reductiveness of models? How can one work with and on models in a creative, productive manner without disavowing power asymmetries and their exclusionary or limiting effects?