Meeting Room: Holmes Hall 472
Day & Time: Wednesdays, 4:30-7:50pm
Professor: Ryan Cordell
Spring Office Hours: Wednesdays 2:30-4pm, Friday 10-11am, and by appointment
“Reading Machines” will pivot around the double valence of its title, outlining a literary history of new media from the hand-press period to the present. Our approach will draw on scholarship in book history, bibliography, media studies, and digital humanities, an intersection described by N. Katherine Hayles and Jessica Pressman as “comparative textual media.”
We will take this comparative, interdisciplinary approach first to better understand machines of reading (e.g. the printed book, the internet) as material, historical, and cultural objects. We will examine how practices of reading, writing, and publishing have interacted—thematically and materially—with contemporaneous technological innovations over the past 250 years. We will complement our readings with praxis, gaining hands-on experience with textual technologies from letterpress (using the English Department’s new letterpress studio) to computer programming, as well as direct experience with archival materials in special collections around Boston. Together, weekly “book labs” and course discussions will help us consider relationships among modes of textual production, reception, and interpretation: including in our purview both “intellectual work,” such as writing, and “manual labor,” such as typesetting.
Through our discussions, we will unpack the second valence of the course title, developing greater capacities to critically read machines, analyzing the political, cultural, and social forces that shape—and are shaped by—textual technologies. We will raise urgent questions around privacy, algorithmic bias, intellectual property, information overload, and textual authority, asking how a rich new media history might inform our technological present and contribute to a richer construction of the digital humanities field. This course will include a substantial introduction to programming in the R language, but presumes no prior technological expertise.
In developing this course I learned from many people, but I particularly thank Whitney Trettien, Anastasia Salter, Matthew Kirschenbaum, and Kari Kraus for graduate syllabi from which I drew particular inspiration.