I am a postdoctoral fellow at Penn State University’s Center for Humanities and Information, specializing in the very early history of computation (pre-1900), Enlightenment studies, Romantic literature, and digital humanities. My work considers what intellectual history can tell us about contemporary technological issues. I also write software that puts my ideas into effect.
In 2018, I received a PhD in English from the Graduate Center, City University of New York. I also have an M.A. in English from NYU and studied literature, mathematics, and computer science at the undergraduate level. Before starting my PhD, I worked for five years in database programming and data visualization.
If you want to get a sense of what my digital work is like, a good place to start is the Distance Machine. The Distance Machine is a web-based program (which you can try in your browser right now) that identifies words in historical texts that were uncommon at particular points in time. The idea is to find the opposite of archaisms—words that seem ordinary to us now, but that had not yet become common at the time when a text was written. I published an article about the project in American Literature; the source code is on GitHub.
I’ve also made some fun things like a poetry generator that can create rhymed verse and a depoeticizer, which makes texts more banal. Most recently, I used a neural network to reconstruct Herman Melville’s novel Moby-Dick from its individual sentences.
I am currently working on a book project, tentatively titled Modernity and the Algorithm, about the history of algorithmic thinking from the seventeenth century to the nineteenth. Focusing on three mathematicians from subsequent centuries—Leibniz, Condorcet, and Boole—I show that the social function of algorithms has varied drastically with changing epistemologies. During the Enlightenment, computation was a politically loaded topic; radicals sought to replace the “errors” of the past with mathematical rationality, while conservatives viewed such methods as tyrannical impositions of arbitrary rules on human thought. As my book shows, the Romantic turn around 1800 enabled mathematicians to skirt these political issues by distinguishing the technical aspects of algorithmic systems from the cultural factors involved in making those systems meaningful to people. This nineteenth-century compromise, I argue, set the terms on which algorithms continue to relate to the user interface in modern computers.