Cyborgs and seismic data art// Moon Ribas

Moon Ribas considers herself a cyborg because of the sensor embedded in her elbow. I consider her a cyborg [data] artist because of how she interprets its output.

What does the sensor do?

Acts as a seventh ‘‘seismic’ sense. It vibrates whenever there’s an earthquake - anywhere in the world. The intensity of that vibration is dependent on the magnitude of the quake, which she begins feeling at 1.0 on the Richter Scale.

What's her interpretation

A performance. Ribas uses her ‘seismic sense’ when performing Waiting for Earthquakes. In this interpretive dance Moon uses movement as her medium to convey what those seismic vibrations feel like. Essentially, she becomes an earthquake made manifest through its data.

Watch for yourself:

first-amend.py

Programmers’ art as
that of natural scientists
is to be precise,
complete in every
detail of description, not

leaving things to chance.
Reader, see how yet
technical communicants
deserve free speech rights;
see how numbers, rules,

patterns, languages you don’t
yourself speak yet,
still should in law be
protected from suppression,
called valuable speech!

The above excerpt is from DeCSS Haiku, a transcoding of DeCSS, which is a piece of software once used to ‘illegally’ decrypt DVDs.

Written by software developer Sech Schoen, the 456-stanza haiku was created to protest the arrest of DeCSS co-creator Jon Lech Johansen, for copyright infringement, and was intended to serve as proof that source code is speech and should be protected under the First Amendment.

I was inspired after reading Gabriella Coleman’s article Code is Speech; which explores various arguments in support of Schoen’s opinion, to make my own attempt at transcoding; only in the opposite direction.

speech >> code.

The below script, which is written using language from the first amendment, prints 'make law'  when unconstitutional = false and the full text of the first amendment on a loop when unconstitutional = true.

import time

acts = ['respects', 'prohibits','abridging','assemble','petition']

violations = ['religion','freedom of','right of']

subjects = ['establishment','free exercise','speech','press', 
'people','petition']

lines = [
'Congress shall make no law respecting an establishment of religion,',
'or prohibiting the free exercise thereof;', 'or abridging the freedom
of speech,','or of the press;', 'or the right of the people peaceably
to assemble, ','and to petition the Government for a redress of 
grievances.'
        ]

unconstitutional = True

def law (): 
    for violation in violations:
        if violation == 'religion':
                for subject in subjects:
                    if subject == 'establishment':
                        for act in acts:
                            if act == 'respects':
                                break
                    
                    elif subject == 'free exercise':
                        for act in acts:
                            if act == 'prohibits':
                                break
                                
        elif violation == 'freedom of':
                for subject in subjects:
                    if subject == 'speech':
                        for act in acts:
                            if act == 'abridging':
                                break
                    elif subject == 'exercise':
                        for act in acts:
                            if act == 'prohibits':
                                break

        elif violation == 'right of':
                for subject in subjects:
                    if subject == 'people':
                        for act in acts:
                            if act == 'assemble':
                                break
                                
                    elif act == 'petition':
                                break

        return lines[0] + lines[1] + lines[2] + lines[3] + lines[4] +
        lines[5] + '\n'

while unconstitutional is True:
    print law()
    time.sleep(.2)
else: 
    print 'make law'

Added In Translation: With Expressions We Traffic

Marissa Kantor Dennis’, With Expressions We Traffic is, in and of itself, an interpretation but it is also a critique of interpretation used in conjunction with therapy as well as an attempt to convey the importance of what can be lost in translation.

Laid out in fragmented columns, the first of which is verbatim an account of what transpired in a clinical encounter between an American doctor, her Spanish-speaking patient and the interpreter who attempts to help them communicate. The second is the author’s commentary on the session outlined in column one. Here she dissects the conversation, adds commentary and points out problems within the framework of having someone interpret during therapy sessions. The third is a reflection from the author where, through quoting and commenting on readings from her works cited, she offers insight into her thought process.

In the introduction, Dennis asks that the reader pays close attention to how they interact with the layout of her writing, asking; where do your eyes go first?; where do they eventually settle?

I started out mindfully read each word in column one before moving to column two, which provided annotations and interpretations that helped me to better understand what had transpired. I tried especially hard to read text that was in Spanish thoroughly before reading the translation and subsequent commentary but found it difficult. I had to fight to read linearly; eventually, I gave up and started jumping around.

I couldn’t understand what was written in Spanish:

Sí, ella es una bruja tam-bién. . . . Y como y me quiso matar como le digo [O: Okay] porque yo soy un millionario [O: mmmhmmm] yo saqué por por eso [fast, garbled] este hospital y los demás hospitales del mundo, y, y negocios que trabajan del mundo están abiertos por mi millón de dólares antes la, de la economía mundial era las torres gemelas entonces un día, yo me golpeé este dedo en la, la bicicleta y me llevaron para el hospital X” allí en el Bronx—ah pues—y me investigaron como tenía el, mi seguro médico y me me salió un millón de dólares [O: okay] entonces investigaron de quién era el millón de dólares y no, no lo reclamó nadie y me lo echaron a mí me llevaron los, entonces me dijeron que me llevaran [inaudible here] . . . y por medio de este millón de dólares me mandaron mis documentos para un shelter ¿se llama X? Aquí, aquí, aquí en Manhattan. Y esas cosas no me quieren entregar eso fue en el 2000. [Ends @ 11:39.]

I was able to understand was the subsequent translation:

Okay, yeah, um, so, the, the Cuban, um, she’s a witch—she’s de nitely a witch. And, um, but, and then I asked him is there, if there was anybody else, and “yes, um, there was, the director of the shelter, this Colombian woman, um, and she tried to kill me, uh, through witchcraft, um, and um, the thing that happened is that, uh, she wants to kill me because I’m a millionaire, um, and it, like, I’m a millionaire, like it all started, um, like several years back, it was, it was, um, it’s because of me and, like, my millions that, um, the hospital, this hospital and all of the hospitals are still open [upswing here]. Because before it was, um, the world economy was based on the twin towers, but then, like, after that, um, it happened that, um, I hurt my  finger one day um and, um, and so I went to the hospital, it was X hospital in the Bronx and they—uh [pause]—they were checking it out and then in the insurance they were checking out the life insurance, and it turned out that, um, that there was a million. And, um, and they were, they, they were checking out the paperwork and figuring out what was going on, and since no one claimed the million dollars, I got the million dollars. And then also, through the paperwork, um, they were giving me a shelter [upswing here] um, which I think he said it was the X shelter, I didn’t quite get the name, um, and, um, and then when I went to get it, like, to get the shelter, like, they wouldn’t give it to me. This was back in 2000—it’s been going on.” [Finish @ 13:16.]

But the translation wasn’t true to what was said:

Carlos begins speaking about Director “R” and talks for over a minute; Olivia doesn’t try to interrupt him… Letting someone talk for one full minute means, most seriously, that the interpretation is not going to be a clinical one, but rather a narrative one, a story of a story, a derivative story, moved from (psychotic) Spanish to (interpreted) English… Look at the linguistic stutters, represented here, poetically disjunctive, by ums and likes and upswings-of-voice that seem to signal uncertainty both of interpretation and original narrative content.

 That last part really stuck with me and I became curious just how many times 'um and 'like' were added in translation. I went through the translated text, found each instance of the two words and augmented them using size and color in order to draw attention to foreign additions made and their implications on what is being said.

like.um.master-1.png

Transgender Lives Matter

Brandon Teena, a 21-year-old trans man, was raped and murdered in Falls City, Nebraska on December 31, 1993. Two men were convicted of first-degree murder in the incident, which became the subject of the Academy Award-winning film Boys Don't Cry.

I don't remember hearing about the murder of Brandon Teena when it happened, in fact until recent years I can't recall seeing any reports about violence against the trans community and.

After watching Boys Don't Cry for the first time and being faced with the, albeit fabricated, brutality faced by Brandon Teena I realized that I had only ever learned a fabricated history of violence against the trans community.

So, I went looking for the details I'd been blind to until now. One of the first things I came across was this list of 'Unlawfully Killed Transgender People.' After reading about how each of the innocent people on that list, were murdered because of their gender identity, I decided to make an interactive to educate others on what the trans community faces simply for wanting to be who they are.

I know it is a small act and in no way comprehensive of everything the trans community deals with, but it is my hope that this interactive will prompt people to further educate themselves on trans issues.

No Love For Latour

Aramis, or The Love of Technology by Bruno Latour is a story told through a combination of fiction and nonfiction, which he calls “scientifictional”. By infusing the nonfictional; interviews, public relations reports, engineer assessments, newspaper articles, and essays, among other sources; with the fictional, a storyline about an engineer and his professor, he hoped to reveal how Aramis, a rapid transit system, failed in the end. Informed by three questions from the book, outlined below, I argue that his approach was ineffective in doing so and offer a potential improvement to his method.

Question 1: Can we unravel the tortuous history of a state-of-the-art technology from beginning to end?

Yes, but just because we can do something doesn't mean we should. While Latour does technically ‘unravel the history of Aramis’ his scientifictional approach buries what is, in my opinion, the most important piece of the story: a clear picture of the network of actors and actants responsible for Aramis’ death; an understanding of who the responsible parties, both human and nonhuman, that caused Aramis to fail are.

Question 2: Can we make the human sciences capable of comprehending the machines they view as nonhuman, and thus reconcile the educated public with bodies it deems foreign to the social realm?

While his use of anthropomorphization makes it easier to see nonhuman contributors as having roles in the social realm, it, like the approach, muddles things and confuses the reader.

Question 3: Can we turn a technological object into the central character of a narrative?

Can we? Yes. Did he do it successfully? No. While all roads lead back to the rapid transit system; we learn about its history; how it would have been used; how it was invented and how it evolved, we never really get a clear picture of what made it fail. We never get an answer to the question "who killed Aramis?" which, was the point of the book.


On improving his method:

How could Latour have made clearer the connections and influences of actor and actant, human and nonhuman in this muddled story?

One possibility is though a visual representation, a network of those responsible for Aramis’ downfall. In order to provide this supplementary learning device, I began to comb through the text and identify the players with the goal of creating a network graph. In my attempt to uncover the underlying network of Latour’s narrative, identifying actors and actants became so difficult that I gave up around page 110, when little more than the magnitude of said complexity and an idea of the actor-actant ratio had been revealed.