Tag Archive for interviews

The Conversation of Culture

Last week I was interviewed on probably the best talk radio program about culture and technology, the CBC’s Spark. The interview grew out of my recent series of blog posts on the topic of algorithmic culture.  You can listen to the complete interview, which lasts about fifteen minutes, by following the link on the Spark website.  If you want to cut right to the chase and download an mp3 file of the complete interview, just click here.focuz.ru

The hallmark of a good interviewer is the ability to draw something out of an interviewee that she or he didn’t quite realize was there.  That’s exactly what the host of Spark, Nora Young, did for me.  She posed a question that got me thinking about the process of feedback as it relates to algorithmic culture — something I’ve been faulted on, rightly, in the conversations I’ve been having about my blog posts and scholarly research on the subject.  She asked something to the effect of, “Hasn’t culture always been a black box?”  The implication was: hasn’t the process of determining what’s culturally worthwhile always been mysterious, and if so, then what’s so new about algorithmic culture?

The answer, I believe, has everything to do with the way in which search engine algorithms, product and friend recommendation systems, personalized news feeds, and so forth incorporate our voices into their determinations of what we’ll be exposed to online.

They rely, first of all, on signals, or what you might call latent feedback.  This idea refers to the information about our online activities that’s recorded in the background, as it were, in a manner akin to eavesdropping.  Take Facebook, for example.  Assuming you’re logged in, Facebook registers not only your activities on its own site but also every movement you make across websites with an embedded “like” button.

Then there’s something you might call direct feedback, which refers to the information we voluntarily give up about ourselves and our preferences.  When Amazon.com asks if a product it’s recommended appeals to you, and you click “no,” you’ve explicitly told the company it got that one wrong.

So where’s the problem in that?  Isn’t it the case that these systems are inherently democratic, in that they actively seek and incorporate our feedback?  Well, yes…and no.  The issue here has to do with the way in which they model a conversation about the cultural goods that surround us, and indeed about culture more generally.

The work of culture has long happened inside of a black box, to be sure.  For generations it was chiefly the responsibility of a small circle of white guys who made it their business to determine, in Matthew Arnold’s famous words, “the best that has been thought and said.”

Only the black box wasn’t totally opaque.  The arguments and judgments of these individuals were never beyond question.  They debated fiercely among themselves, often quite publicly; people outside of their circles debated them equally fiercely, if not more so.  That’s why, today, we teach Toni Morrison’s work in our English classes in addition to that of William Shakespeare.

The question I raised near the end of the Spark interview is the one I want to raise here: how do you argue with Google?  Or, to take a related example, what does clicking “not interested” on an Amazon product recommendation actually communicate, beyond the vaguest sense of distaste?  There’s no subtlety or justification there.  You just don’t like it.  Period.  End of story.  This isn’t communication as much as the conveyance of decontextualized information, and it reduces culture from a series of arguments to a series of statements.

Then again, that may not be entirely accurate.  There’s still an argument going on where the algorithmic processing of culture is concerned — it just takes place somewhere deep in the bowels of a server farm, where all of our movements and preferences are aggregated and then filtered.  You can’t argue with Google, Amazon, or Facebook, but it’s not because they’re incapable of argument.  It’s because their systems perform the argument for us, algorithmically.  They obviate the need to justify our preferences to one another, and indeed, before one another.

This is a conversation about culture, yes, but minus its moral obligations.

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