In my previous post I addressed the question, who speaks for culture in an algorithmic age? My claim was that humanities scholars once held significant sway over what ended up on our cultural radar screens but that, today, their authority is diminishing in importance. The work of sorting, classifying, hierarchizing, and curating culture now falls increasingly on the shoulders of engineers, whose determinations of what counts as relevant or worthy result from computational processes. This is what I’ve been calling, “algorithmic culture.”
The question I want to address this week is, what assumptions about culture underlie the latter approach? How, in other words, do engineers — particularly computer scientists — seem to understand and then operationalize the culture part of algorithmic culture?
My starting point is, as is often the case, the work of cultural studies scholar Raymond Williams. He famously observed in Keywords (1976) that culture is “one of the two or three most complicated words in the English language.” The term is definitionally capacious, that is to say, a result of centuries of shedding and accreting meanings, as well as the broader rise and fall of its etymological fortunes. Yet, Williams didn’t mean for this statement to be taken as merely descriptive; there was an ethic implied in it, too. Tread lightly in approaching culture. Make good sense of it, but do well not to diminish its complexity.
Those who take an algorithmic approach to culture proceed under the assumption that culture is “expressive.” More specifically, all the stuff we make, practices we engage in, and experiences we have cast astonishing amounts of information out into the world. This is what I mean by “cultural informatics,” the title of this post. Algorithmic culture operates first of all my subsuming culture under the rubric of information — by understanding culture as fundamentally, even intrinsically, informational and then operating on it accordingly.
One of the virtues of the category “information” is its ability to link any number of seemingly disparate phenomena together: the movements of an airplane, the functioning of a genome, the activities of an economy, the strategies in a card game, the changes in the weather, etc. It is an extraordinarily powerful abstraction, one whose import I have come to appreciate, deeply, over the course of my research.
The issue I have pertains to the epistemological entailments that flow from locating culture within the framework of information. What do you have to do with — or maybe to — culture once you commit to understanding it informationally?
The answer to this question begins with the “other” of information: entropy, or the measure of a system’s disorder. The point of cultural informatics is, by and large, to drive out entropy — to bring order to the cultural chaos by ferreting out the signal that exists amid all the noise. This is basically how Google works when you execute a search. It’s also how sites like Amazon.com and Netflix recommend products to you. The presumption here is that there’s a logic or pattern hidden within culture and that, through the application of the right mathematics, you’ll eventually come to find it.
There’s nothing fundamentally wrong with this understanding of culture. Something like it has kept anthropologists, sociologists, literary critics, and host of others in business for well over a century. Indeed there are cultural routines you can point to, whether or not you use computers to find them. But having said that, it’s worth mentioning that culture consists of more than just logic and pattern. Intrinsic to culture is, in fact, noise, or the very stuff that gets filtered out of algorithmic culture.
At least, that’s what more recent developments within the discipline of anthropology teach us. I’m thinking of Renato Rosaldo‘s fantastic book Culture and Truth (1989), and in particular of the chapter, “Putting Culture in Motion.” There Rosaldo argues for a more elastic understanding of culture, one that refuses to see inconsistency or disorder as something needing to be purged. “We often improvise, learn by doing, and make things up as we go along,” he states. He puts it even more bluntly later on: “Do our options really come down to the vexed choice between supporting cultural order or yielding to the chaos of brute idiocy?”
The informatics of culture is oddly paradoxical in that it hinges on a more and less powerful conceptualization of culture. It is more powerful because of the way culture can be rendered equivalent, informationally speaking, with all of those phenomena (and many more) I mentioned above. And yet, it is less powerful because of the way the livingness, the inventiveness — what Eli Pariser describes as the “serendipity” — of culture must be shed in the process of creating that equivalence.
What is culture without noise? What is culture besides noise? It is a domain of practice and experience diminished in its complexity. And it is exactly the type of culture Raymond Williams warned us about, for it is one we presume to know but barely know the half of.