Meetings with Books: Special Collections in the 21st Century is a recent publication of the McGill University Library and Archives that emerged from a 2013 conference focused on Raymond Klibansky’s library. Despite its rather minimalist looking book-cover (you can’t always judge…), the print volume is very impressive (as an object, in addition to its stimulating content). As I said to co-editor Jillian Tomm, it oozes craft and care. I’m also delighted to say that there’s an open access digital version of it (that’s very convenient and free but doesn’t do justice to the quality of the print volume).
I have a contribution in the collection entitled “Thinking Bigger: Reflections on the Digital” that can be downloaded separately as a PDF). Here’s a brief excerpt:
Quantitative and algorithmic analyses represent just one component of larger intellectual and hermeneutical processes. If computational analysis isn’t the end, but a means to the discovery of previously unknown materials, or to a proliferation of representations of a cultural object that can lead to new observations, new associations, and new arguments, then digital methodologies take on a new significance. Indeed, not using computational techniques becomes a deliberate move to exclude other potential materials and perspectives. Lack of time and expertise may be justifiable defenses, but we would otherwise look with great suspicion on a scholar who knowingly refuses to consider possible sources of insight.
Thinking bigger with the digital means (re)calibrating our expectations of computational methodologies. Dismissing the computer outright from skepticism or fear may be unfortunate, but exaggerated notions of what the computer can do are equally damaging, inevitably leading to confusion and disillusionment. We are so habituated to the ubiquitous and prodigious efficiency of computers in various aspects of our lives (search engines and mapping applications, for instance)—no to mention representations of artificial intelligence in science fiction literature and film—that it is all too easy to assume that they are able to do more than they can.
Fundamentally, computers don’t understand language, they process it. Once that is fully recognized and understood, the respective roles of the computer and the human become easier to delineate. Computers have prodigious capabilities for storing, processing, and generating data. In contrast, humans are slow and unreliable, but have idiosyncratic reservoirs of knowledge and experiences that can interact with cultural artifacts to produce unique perspectives. It makes no sense for us to ask computers to interpret texts or produce insights for us, that’s our job. Computers can serve to exceed the reach of human grasp, in terms of both quantity (how much information is accessed) and quality (how the information is represented). The computer reflects what we ask of it, as mechanically or as creatively as we choose, the onus is on us to use it in ways that are compatible with our epistemological framework.