When we talk about algorithms, we never talk about the person, we talk about the systems they operate on, the systems they facilitate, and then the eventual consequences that fall when they supposedly ‘malfunction’. Throwing this out into twitter, a friend and talented creative technologist Dan Williams succinctly reminded me that we should always be replacing the word ‘algorithms’ with ‘a set of instructions written by someone.’ They are made, and written, by human beings, just like all technology is (a general statement, I know, but it all began with us). By removing that element when talking about them we cease to have any understanding of the culture and social systems behind it, which arguably are the reasons why algorithms are having such a huge impact on our lives. If we’re going to have constructive conversations about the cultural and societal impact of algorithmically mediated culture, we have to always remember that there are humans in it, and not just at the other end of the black box feeling the vibrations. As Matthew Plummer-Fernandez pointed out in a panel on Data Doubles this year, the problems with confronting complex computation systems demands a socio-technical, not a purely technical solution.
This reminds me of a recent post I wrote about Andrew Piper’s current project and other projects in the digital (or computational) humanities. I’ve been thinking a lot about how to evaluate projects such as Andrew’s, and Kane’s post made me realize the extent to which I default to thinking about outcomes, results, answers — and not so much about the originating questions, the “set of instructions written by someone.”
Twenty years ago, Mark Edmundson commented that “Paul de Man is a more difficult critic to read and understand than a responsive, rather impressionistic essayist like Virginia Woolf. But one can teach intelligent students to do what de Man does; it is probably impossible to teach anyone to respond like Woolf if he has little aptitude for it.” Edmundson goes on to ask, “And how could we sustain the academic study of literature if we were compelled to say that a central aspect of criticism is probably not teachable?” — but while that’s an important question it’s not the one I want to pursue right now.
Rather, I’d like to focus on the indefinable skill he’s referring to here, which is, I think, what some people used to call critical tact — the knack for perceiving what themes or questions will, upon pursuit, yield fruitful thoughts. It seems to me that this tact is no less valuable in computational humanities work than in any other kind of critical work, and that we would do well to think about what the best questions look like, what shape or form they tend to take.
Edmundson is probably right to suggest that critical tact can’t be taught, but it can nevertheless be learned (no one is born with it). And maybe one way people in DH could learn it is by spending a lot of time thinking about and debating this: Who asks the best questions? Who writes the most provocative and fruitful instructions?