From Page to Algorithm: Reading, Writing, and Scholarship in the Age of Data

Today’s contentious debates about the cultural and pedagogical impacts of generative AI downplay a prior and arguably equally impactful shift in our scholarly and teaching activities represented by the massive troves of digitized text that make generative AI possible. In just a few decades, we’ve gone from doing almost all of our writing, reading, research, and teaching on paper to doing almost none of it on paper, and all of it on laptops, tablets, and phones, through the exchange of digital files, using algorithmic tools like search engines to navigate, discover, organize, and interpret the digitized and born-digital content we now almost exclusively work with. The databases, digital repositories, along with the tools and processes that make the cultural and literary works held in them readable and analyzable – or that fail to do so –, from digitization itself to search tools to data-oriented analysis to digital publication platforms, have redefined these materials and our relations as scholars to them. Keywords and algorithms delivering snippets and clusters mediate our access and potentially our understanding more than long-standing bibliographic categories like authors, titles, and works. What is scholarly work in the digital age? What new forms of research and publication are taking shape? What new skills and techniques should we be learning? And what are the implications for the established values and conventions of print-era scholarship, which continue to dictate our methods of evaluation: authorship, citation, originality, close reading, and interpretation, among others?

In this micro-seminar, we’ll explore the impacts and consequences of this shift. We’ll think methodologically and theoretically about these impacts and explore strategies and techniques for better working in our still relatively new digital framework.