This week’s readings expressed a wide and deeply conflicted range of attitudes regarding the assorted uses of computers, computer modeling and the data-ization of the humanities. The authors were all for it, but some of the arguments against the idea they discussed were interesting – and valid. This validity is incredibly important; having been discussing diversity and cultural inclusion on LBSC 631 this week, I found myself hyper-aware of the attitudes some of the authors were displaying to their techno-tentative brethren. However, this is a blog and I’m am going to make some grand and sweeping statements – which I will then try to back up… hopefully using memes.
Grand Statement #1: Let’s not be that guy.
You know the guy I mean.
Grand Statement #2: “Computers allow you to go further.”
If there is to be a rallying cry for the Digital Humanities, this might well be it. Yesterday, I was whining to a mechanical engineer of my acquaintance about Underwood’s observations of the reluctance in the Academy to embrace digital technologies, how they fear a total seismic shift* in their world.
I would like to assuage those fears. According to my mechanical engineer, “Computers allow you to go further. They don’t take away the work.” I was scrambling for a pen here so the next bit is a paraphrase: computers make more work and they make what you’ve got more accessible.
Take the work done with MALLET, Blevins describes how computer modeling validates itself. The Ballard diary, chosen in part one assumes for its completeness, shows how well the computer can model. Blevins even relates how surprised he was that it initially worked so well. But it worked. The tool did the thing it was designed to do. That’s great! And now there’s all this data to play with. If you wanted to only focus on the number of babies born when the crocuses were in bloom, then it’s a simple matter of correlating your data. If you want to take up the argument discussed in Graphs, Maps, and Trees, that there is no such thing as a “gothic novel” and dissolve that grouping from his chart of genres to see what the effects are, you can do so. Vistas abound, new peaks arise to be surmounted.
The problem, I think, is that Humanists see things like “correlating data” and “data manipulation” and they freak out because these are STEM things. That they are not scientists, but humanists. Theirs is a world of logic and rhetoric. Well, yes, fine, but notice how scientists get all the grants?
We don’t need to spend years waiting on graduate students to count everything by hand. We can load that puppy, or important literary work, into a computer and run analysis, any analysis, all analyses. And then tomorrow, we can do it again, go further and deeper. Instead of relying on grad students, you can partner with other academics on the other side of the world as easily as in the next building over a la Graham, Milligan, and Weingart. Where privacy and exclusivity are a concern, there is no need to make work public as they did, but this opens a work up to more input, catching mistakes earlier, and examining multiple points of view since no one publishes the book to make money anyway. You publish the book to get tenure.
Grand Statement #3: This is not the Singularity.
Technology is moving at a brisk clip, but we’re not in any danger of be replaced by robots today or tomorrow or the next day. For whatever reason, and I’m going to guess it has a lot to do with not being good with computers 10+ years ago, some humanists aren’t on board with putting the digital into their work. This is a massive disappointment for the rest of us because the kind of work that they’re doing, work like breaking down the linguistic anachronisms in Downton Abbey (a point of much personal vindication for me) and examining the Ballard diary, is really interesting. And doing it with graphs means that people who don’t have PhDs can understand it too. Perhaps therein lies the fear; that if outsiders can see – and understand – what we’re doing, we’ll all revert to the seventh grade and get made fun of by the popular kids for liking to evaluate complexly and dig a little deeper. So how do we embrace our intelligence, how do we share the fruits of our enthusiasm in the best possible way? I would argue that charts and graphs – visualizations of complex data – are the way forward.
*To be fair, the idea of a seismic shift as representative of a complete overhaul of any working system was no doubt active before Mr. M. Watkins published his article “How Managers become Leaders,” but it is from him that I got the idea so I have linked to it in Google Scholar: Michael D. Watkins, “How Managers Become Leaders,” Harvard Business Review 90 (June 2012), 65-72.