Glitch, Circuit Bending & Breaking as a Way of Knowing

A big idea in the digital humanities is that building is a hermeneutic, an iterative interpretive process that leads toward knowing and understanding. I saw this great video on The Art of Glitch toady that made me think a bit more about how much breaking can is an essential related way of knowing. I realize I’m not necessarily breaking any new ground here, but I think these few examples I’ve pulled together do a nice job at getting at what it is we learn when we break the slick world of computing a bit.

You should watch the whole thing, its’ great (you should also watch their video on Animated Gifs). But the part that I found most compelling was Scott Fitzgerald‘s basic demonstration of how to glitch some files (change a .mp3 to a .raw and open it in photoshop or open a .jpg in a text editor and delete some chunks of it. It’s fun, in that it is something you can follow along at home with, but the act of doing these things actually teaches something about the nature of digital files. He does a good job of explaining this in the following statement.

“Part of the process is empowering people to understand the tools and underlying structures you know what is going on in the computer. As soon as you understand the system enough to know why you’re breaking it then you have a better understanding of what the tool was built for.”

In short, breaking the files exposes their logic. In a way it helps us escape screen essentialism and see a different side of the nature of the files, file formats, compression algorithms, and structure of digital objects. The whole experience reminded me that I never got around to sharing some of the amazingly cool exhibit on circuit bending at Milwaukee’s Discovery Zone.

Breaking and Bending the Hardware

Circuit Bending at Discovery Zone

If you are unfamiliar, here is how Wikipedia describes Circuit Bending.

Circuit bending is the creative customization of the circuits within electronic devices such as low voltage, battery-powered guitar effects, children’s toys and small digital synthesizers to create new musical or visual instruments and sound generators.

Here is a little video I took of messing with the dials on the bent NES.

In this case, messing with the hardware is producing glitches. In this case, the artist (Luke Reddington) bent a series of different devices. He went in and put a bunch of toggles on this NES that lets you flip a bunch of different switches inside the device that no one is supposed to be messing around with.

In my mind, this works just the same as changing the file extensions. When you poke around inside the Nintendo and set a few different switches to toggle things that aren’t supposed to be toggled you can get this. Sure it’s art, there is an aesthetics to the whole thing, but there is also an element of coming to know in here. I think these are all examples of the ways in which breaking is as much a way of knowing as building.

Breaking & Bending as Knowing & Learning about the Machine

In each case, much like what happens when you set an augmented reality app like wordlens to the wrong language and have it try and read things that aren’t text, or when you go on a quest to find oddities in the digitized corpus of google books, circuit bending and glitch art draw out attention away from the way things are intended to be presented, away from being seemless things that obfuscate their nature, and get us to peek behind the curtain of the technologies and see a bit of the logic of computing.

Defining Data for Humanists: Text, Artifact, Information or Evidence?

Fred and I got some fantastic comments on our Hermeneutics of Data and Historical Writing paper through the Writing History in the Digital Age open peer review. We are currently working on revising the manuscript. At this point I have worked on a range of book chapters and articles and I can say that doing this chapter has been a real pleasure. I thought the open review process went great and working with a coauthor has also been great. Both are things that don’t happen that much in the humanities. I think the work is much stronger for Fred and I having pooled our forces to put this together. Now, one the comments we got sent me on another tangent. One that is too big of a thing to shoe horn into the revised paper.

On the Relationship Between Data and Evidence

We were asked to clarify what we saw as the difference between data and evidence. We will help to clarify this in the paper, but it has also sparked a much longer conversation in my mind that I wanted to share here and invite comments on. As I said, this is too big of a can of worms to fit into that paper, but I wanted to take a few moments to sketch this out and see what others think about it.

What Data Is to a Humanist?

I think we have a few different ways to think about what data actually is to a humanist. I feel like thinking about this and being reflexive about what we do with data is a really important thing to engage in and here is my first pass at some tools for thought about data for humanists. First, as constructed things data are a species of artifact. Second, as authored objects created for particular audiences, data can be interpreted as texts. Third, as computer processable information data can be computed in a whole host of ways to generate novel artifacts and texts which themselves open to interpretation and analysis. This gets us to evidence. Each of these approaches, data as text, artifact, and processable information, allow one to produce/uncover evidence that can support particular claims and arguments. I would suggest that data is not a kind of evidence but is a thing in which evidence can be found.

Data are Constructed Artifacts

Data is always manufactured. It is created. More specifically, data sets are always, at least indirectly, created by people. In this sense, the idea of “raw data” is a bit misleading. The production of a data set requires a set of assumptions about what is to be collected, how it is to be collected, how it is to be encoded. Each of those decisions is itself of potential interest for analysis.

In the sciences, there are some agreed upon stances on what assumptions are OK and given those assumptions a set of statistical tests exist for helping ensure the validity of interpretations. These kinds of statistical instruments are also great tools for humanists to use. However, they are not the only way to look at data. For example, most of the statistics one is likely to learn have to do with attempting to make generalizations from a sample of things to a bigger population. Now, if you don’t want to generalize, if you want to instead get into the gritty details of a particular individual set of data, you probably shouldn’t use statistical tests that are intended to see if trends in a sample are trends in some larger population.

Data are Interpretable Texts

As a species of human made artifact, we can think of datasets as having the characteristics of texts. Data is created for an audience. Humanists can, and should interpret data as an authored work and the intentions of the author are worth consideration and exploration. At the same time, the audience of data is also relevant, it is worth thinking about how a given set of data is actually used, understood and how data is interpreted by audiences that it makes its way to. That could well include audiences of other scientists, the general public, government officials, etc. In light of this, one can take a reader response theory approach to data.

Data are Processable Information

Data can be processed by computers. We can visualize it. We can manipulate it. We can pivot and change our perspective on it. Doing so can help us see things differently. You can process data in a stats package like R to run a range of statistical tests, you can do like Mark Sample and use N+7 on a text. In both cases, you can process information, numerical or textual information, to change your frame of understanding a particular set of data.

Data can Hold Evidentiary Value

As a species of human artifact, as a cultural object, as a kind of text, and as processable information data is open to a range of hermeneutic processes of interpretation. In much the same way that encoding a text is an interpretive act creating, manipulating, transferring, exploring and otherwise making use of a data set is also an interpretive act. In this case, data as an artifact or a text can be thought of as having the same potential evidentiary value of any kind of artifact. That is, analysis, interpretation, exploration and engagement with data can allow one to uncover information, facts, figures, perspectives, meanings, and traces which can be deployed as evidence to support all manner of claims and arguments. I would suggest that data is not a kind of evidence; it is a potential source of information which could hold evidentiary value.