Overview
I am an associate professor of German, founding director of the Digital Theory Lab, and Director of Digital Humanities at NYU. My research focuses on literary theory, digital culture, and the history of science. Special issues of concern are dialectics, semiotics, the nature of data and computing, and problems of political economy after the Industrial Revolution.
I am the author of Transplanting the Metaphysical Organ: German Romanticism between Leibniz and Marx (Fordham 2016), which is a history of the term “organ” in German Romanticism, the main argument of which is that Romantic literary theory and philosophy created the first technological metaphysics by combining speculative philosophy and incipient life science.
My second monograph, Language Machines: Cultural AI and the End of Remainder Humanism will be published by the University of Minnesota press in spring 2025. This book argues that generative AI is cultural, not cognitive, and that it is especially structuralist linguistic theory that is both embodied by the new algorithms and needed to interpret them critically. Blending media analysis with literary theory, Language Machines proposes that computation and language – as separate systems of representation – have been synthesized apart from cognition to produce and unprecedented “algorithmic reproducibility of language.” Public versions of some of the book’s arguments may be found in Jacobin here and here, and in the Boston Globe here.
I have two ongoing book projects. First is Artificial Concepts: How Cybernetics Encountered German Idealism – a history of German Idealism’s neglected and outsize role in the creation of the digital universe, cognitive science, and AI. The other, The Mismeasure of Mind: Against the Prediction of Everything (under contract at W.W. Norton), argues that we are addicted to prediction, stewing in a relativism bred by overconfidence on the part of psychologists and behavioral scientists in their statistical models of mind, and advocates the dismantling of the “belief-industrial complex.” One argumentative thread of the book appeared in the New York Times, and another in this review in The Point.
In 2018, I founded the Digital Theory Lab which pursues theoretical insights in digital media through a hands-on and collaborative Lab setting. The Lab seeks to synthesize technical approaches of data science and humanities disciplines, as may be seen in the Lab’s special issue of Critical Inquiry on “Surplus Data.” With a particular focus on the history of computation and the emergence of deep learning and generative AI, the Lab is a collaborative learning space in which graduate students and professors experiment with the goal of creating new theory grounded in the technological conditions of the present.
I also write more broadly about American culture, as in this profile of Aaron Rodgers for The Point magazine.
Research Focus
The Mismeasure of Mind and the Scale of Probability
My intention is to complete the manuscript of The Mismeasure of Mind: Against the Prediction of Everything during the fellowship year at the Society. This book, under verbal contract (announced on Publishers Marketplace) with Norton, is a critical and historical polemic about the scale of probability. Both in depth and in breadth, everything we do now is not just “quantified” – as critiques of wearables, Big Data, and self-optimization tell us – but modeled. Models predict which word you will type, which mortgage you will and should choose, and how
you will react to “content” online. Underlying every model is an unfathomably large vector of data – a hypothesis that takes material form and congeals in front of you as a nudge, a suggestion, a manipulation of your behavior. From Alan Turing’s use of Bayes’ formula to crack the Nazi Enigma code using early computing engines, our society was set on a path of crunching amounts of data that we cannot distinguish mentally in any meaningful way to do menial and often regressive tasks that help secure wealthy and security for the very few. My book is meant to cut across this scale by narrating the history of Bayesian methods, modeling, and the misconstrual of the human mind and the human as such that have resulted from it.