Fabian Offert: Vector Media

For the inaugural Sunrise Lecture on Media and Technology, hosted by the Department of German, we welcome Dr. Fabian Offert, Assistant Professor of the History and Theory of Digital Humanities at the University of California, Santa Barbara.

Dr. Offert will also host a workshop open to graduate students of all departments on March 14, 10:00-12:00 in Dwinelle 188. Please sign up for the workshop here.

Vector Media 

The capability of neural networks to generate texts and images by learning from large amounts of data is often framed as both the most significant contribution and the most obvious flaw of contemporary artificial intelligence research. Much critical work thus starts from a reading of training datasets – but the mapping from training data to trained model is always messy and indirect. Bias is not just a question of what is represented but also of the logic of representation itself, of the peculiar ways of knowing that emerge from training neural networks on unprecedented amounts of multimodal data. 

Vector Media considers the ideological charge of these peculiar ways of knowing and thus writes a new historical epistemology of generative artificial intelligence. It reframes artificial intelligence systems as determined by a central, overarching paradigm: that the production of new knowledge can be operationalized as a geometric interpolation between fragments of existing knowledge. Vector mathematics, of the kind employed in the famous analogy query of natural language processing, “men + king = woman + ?”, is imagined as a tool to achieve this – but its prerequisite is the elimination of all media specificity, going far beyond the kind of alignment required by mere digitization. We are used to technologies creating new (or emulating old) media. Artificial intelligence systems are instead designed to collapse all media into a universal space of commensurability, the vector space, enabling their circulation, translation and manipulation within artificial intelligence infrastructures. 

Following a trail of newly uncovered ideas about neural representation in the technical literature, from early attempts to model the human visual cortex to contemporary multimodal foundation models, Vector Media reconstructs how the subcutaneous ideology of the vector space came to dominate artificial intelligence research, how it informs the expansion of artificial intelligence into all areas of everyday life (as well as the natural sciences), and how it ultimately must be understood as a tool for the creation of neural exchange value: value that specific cultural objects obtain once they become part of a vector space, and that exists exclusively as a function of their neural commensurability.