If there is one thing this week has taught us, it is that the debate of computational studies in literary analysis continues to rage. Underwood's argument (March 27 2019) argues that "advances in computing" are going to create a new opportunity for the field, an avenue that makes us marketable to undergraduate audiences, rewrites the 20th century model that leaves the fun, new questions to the scientists and creates an arena that is interdisciplinary. His article changes the perspective of the humanities losing ground to the sciences to one where the disciplines can work together to reward curiosity of the past. Underwood's position seems optimistic to me and in reality, I agree with Da a little more than Underwood. I think we can use CLS to enhance learning systems, but I think we need to be careful about how we use CLS, especially big data (everyone recently in the sciences seems to be turning to big data to do more (I'm having doubts, clearly). I'm thinking about how in petroleum engineering, there's a call to use big data to process complex questions that traditional computational analysis lacks for conventional drilling and I think there's danger there because even if it is using a thousand variables, with so many, we lack the ability to suss out the specific complexities that yield to new form and new discoveries; that's my biggest beef).
I also found Underwood and Risam's articles illuminating. In Underwood, he takes up the issue of periodization and the potential of historical continuity. Underwood (164) speculates the reasons for the objections to quantification in literary science, but what I find interesting is that by end of his argument addressing Romanticism (169), I agree with him. Perhaps periodization fails to acknowledge the complexity of certain cultural trends and moments and quantification offers an opportunity to reexamine old questions. Well, I fell in love with Risam's description: "the opportunity to intervene in the digital cultural record--to tell new stories, shed light on counter-histories, and create spaces for communities to produce and share their own knowledge should they wish--is the great promise of digital humanities (5). That is the most optimistic description I've heard, especially since many--as Risam later notes-- compare it to the cultural wars (theory) and have DH killing humanities. Risam also takes up the issue that the issues prominent in post-colonialism--exclusions and biases, a refusal to acknowledge politics and racial privilege--have reproduced in digital knowledge production (139); his work shows how groups are beginning to combat that and I find that uplifting as well as enlightening. I must admit I found the debate more fascinating, but I found these pieces integral to my understanding of how complex the field of DH is becoming and how it has the potential to revolutionize our discipline.