This is something of a follow-up on my last post, where I concluded by suggesting that we might need a “data humanities” and a “data rhetoric” that paralleled the emergence of data science. I should probably say first that I don’t mean this as a replacement for terms like digital rhetoric or digital humanities. It’s probably closer to a specialization within those umbrella terms but all these things are such interdisciplinary mash-ups anyway.
If you squint your eyes a little, you can see that data science has been around for a long time. You could say that it is statistics plus computer science. You could look at cryptanalysis in WWII as data science I suppose. You could look at cybernetics or information science as data science. Moneyball, Freakonomics, and the 538 blog could all be examples of data science. On the other hand, data science is something new. It was a termed “coined” in 2008 by D.J.. Patil and in this decade we’ve begun to see an explosion of jobs for people with the title “data scientist.” If you want to know more, here’s a Forbes article on “The Rise of the Data Scientist” and another in the Harvard Business Review that proclaims “Data Scientist: The Sexiest Job of the 21st Century.” Basically though, data scientists respond to a recognizable challenge. We are collecting increasing amounts of data. How do we make sense of it? And from a business perspective, how do we monetize it?
During this period, methods in the digital humanities variously called distant reading, macroanalysis, cultural analytics, and so on represent efforts within the humanities that run parallel to data science, calling on the same computational methods. Similar work has also been done in rhetoric and composition, though with less fanfare or controversy in the Chronicle of Higher Education. I would broadly characterize these efforts as using data scientific methods to explore traditional objects of study and often ask fairly conventional research questions. If that sounds like a criticism then I have not expressed myself well. I think this is valuable and interesting work (and something I might pursue once I’m done with my current book project). Here are two curiously related examples, “Finding Genre Signals in Academic Writing” by Ryan Omizo and Bill Hart-Davidson in the Journal of Writing Research and “The Life Cycles of Genres” by Ted Underwood in the Journal of Cultural Analytics. Each obviously investigates genres, one from a rhetoric perspective and the other from a literary standpoint. A comparison of these two might make for an interesting blog post, but not today. In any case, work like this is certainly part of what a data humanities/data rhetoric looks like.
It we might reduce that to the data-analysis of the humanistic/rhetorical objects of study, then we can also observe the inverse, which is the cultural-rhetorical critique of data. That work also has its value, and there’s plenty of it. That’s something our disciplines already know how to do very well. It’s basically about turning one’s critical lens onto this particular subject matter.
Predictably, my interest here is in something tangential to those two scholarly moves. And (equally predictably) it begins with new materialist ontological premises about the space humans and nonhumans share and the emergence of cognitive, expressive, and rhetorical capacities in the relations among us all in that space. And then it turns to something like Mark Zuckerberg’s February 16th announcement about his vision for Facebook. It’s nearly 6000 words long, but here’s the thesis: “In times like these, the most important thing we at Facebook can do is develop the social infrastructure to give people the power to build a global community that works for all of us.” Holy hell and good intentions Batman! Think about it this way. How has the lived experience of human life, the communities we’ve grown, the knowledge we’ve constructed and shared, the material culture we’ve built, and the effects of all of that on our planet been shaped over the last 500 years by the social-technological-informational infrastructure of print media? Ask that same question about the last 5000 years and writing. Now ask it about computers and the last 50 years. Or “big data” and the last 5 years. Hell, ask it about big data and the last five months!
Yes, we need to figure out how to use data-analytical methods, and yes, we should continue to employ cultural-rhetorical critical methods to study these phenomena. But I think there’s more. We might investigate and experiment with emerging rhetorical capacities of these media-turned-data ecologies. I really wish I could tell you what that means, but I think the best I can come up with is that it will require a significant degree of openness. What I would consider the underlying ontological/compositional questions of rhetoric would remain with us. That is, how do our encounters with the expressive forces of data ecologies foster rhetorical and cognitive capacities? How would we describe those capacities? How might we recursively shape those capacities through technological design, institutional structures, laws, ethics, pedagogies, genres, and other individual and community practices?
I’ll try to end this with something concrete by returning to Zuckerberg’s discussion of Facebook as a “civically-engaged community.”
There are two distinct types of social infrastructure that must be built:The first encourages engagement in existing political processes: voting, engaging with issues and representatives, speaking out, and sometimes organizing. Only through dramatically greater engagement can we ensure these political processes reflect our values.The second is establishing a new process for citizens worldwide to participate in collective decision-making. Our world is more connected than ever, and we face global problems that span national boundaries. As the largest global community, Facebook can explore examples of how community governance might work at scale.